Datasets:

allenai

/

SciRIFF

like 32

Follow

Ai2 1,383

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: related work Context before the citation: Although originally developed as a tool to assist in query formulation, Booth (2000) pointed out that PICO frames can be employed to structure IR results for improving precision. Cimino and Mendonc¸a reported good performance for etiology, diagnosis, and in particular therapy, but not prognosis. The goal was to automatically classify citations for task-specific retrieval, similar in spirit to the Hedges Project (Haynes et al. 1994; Wilczynski, McKibbon, and Haynes 2001). Citation Sentence: Although originally developed as a tool to assist in query formulation , Booth ( 2000 ) pointed out that PICO frames can be employed to structure IR results for improving precision . Context after the citation: PICO-based querying in information retrieval is merely an instance of faceted querying, which has been widely used by librarians since the introduction of automated retrieval systems (e.g., Meadow et al. 1989). The work of Hearst (1996) demonstrates that faceted queries can be converted into simple filtering constraints to boost precision. The feasibility of automatically identifying outcome statements in secondary sources has been demonstrated by Niu and Hirst (2004). Their study also illustrates the importance of semantic classes and relations.

Background

acl_arc_intent_classification:train:38

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: method Context before the citation: In our case, the clustering is performed by the program Snob, which implements mixture modeling combined with model selection based on the Minimum Message Length (MML) criterion (Wallace and Boulton 1968; Wallace 2005). The idea behind the Doc-Pred method is similar to Bickel and Scheffer’s (2004): Response documents are grouped into clusters, one of these clusters is predicted for a new request on the basis of the request’s features, and the response that is most representative of the predicted cluster (closest to the centroid) is selected. Hence, we keep their representation at a low level of abstraction (bag-of-lemmas). Citation Sentence: In our case , the clustering is performed by the program Snob , which implements mixture modeling combined with model selection based on the Minimum Message Length ( MML ) criterion ( Wallace and Boulton 1968 ; Wallace 2005 ) . Context after the citation: We chose this program because the number of clusters does not have to be specified in advance, and it returns a probabilistic interpretation for its clusters (this interpretation is used by the Sent-Pred method, Section 3.2.2). The input to Snob is a set of binary vectors, one vector per response document. The values of a vector correspond to the presence or absence of each (lemmatized) corpus word in the document in question (after removing stop-words and words with very low frequency).4 The predictive model is a Decision Graph (Oliver 1993), which, like Snob, is based on the MML principle. The Decision Graph is trained on unigram and bigram lemmas in the request as input features,5 and the identifier of the response cluster that contains the actual response for the request as the target feature.

Uses

acl_arc_intent_classification:train:380

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: related work Context before the citation: The third approach to cross-lingual retrieval is to map queries and documents to some intermediate representation, e.g latent semantic indexing (LSI) (Littman et al, 1998), or the General Vector space model (GVSM), (Carbonell et al, 1997). Sanderson, 1994 studied the issue of disambiguation for mono-lingual M. Other studies on the value of disambiguation for cross-lingual IR include Hiemstra and de Jong, 1999; Hull, 1997. Citation Sentence: The third approach to cross-lingual retrieval is to map queries and documents to some intermediate representation , e.g latent semantic indexing ( LSI ) ( Littman et al , 1998 ) , or the General Vector space model ( GVSM ) , ( Carbonell et al , 1997 ) . Context after the citation: We believe our approach is computationally less costly than (LSI and GVSM) and assumes less resources (WordNet in Diekema et al., 1999).

CompareOrContrast

acl_arc_intent_classification:train:381

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: experiments Context before the citation: Many provide graphical user interfaces (GUI) for manual annotation (e.g. General Architecture for Text Engineering (GATE) (Cunningham et al., 1997) and the Alembic Workbench (Day et al., 1997)) as well as NLP tools and resources that can be manipulated from the GUI. There are a number of generalised NLP systems in the literature. Citation Sentence: Many provide graphical user interfaces ( GUI ) for manual annotation ( e.g. General Architecture for Text Engineering ( GATE ) ( Cunningham et al. , 1997 ) and the Alembic Workbench ( Day et al. , 1997 ) ) as well as NLP tools and resources that can be manipulated from the GUI . Context after the citation: For instance, GATE currently provides a POS tagger, named entity recogniser and gazetteer and ontology editors (Cunningham et al., 2002). GATE goes beyond earlier systems by using a component-based infrastructure (Cunningham, 2000) which the GUI is built on top of. This allows components to be highly configurable and simplifies the addition of new components to the system. A number of stand-alone tools have also been developed.

Background

acl_arc_intent_classification:train:382

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: experiments Context before the citation: The keypoints are clustered into 5,000 visual codewords (centroids) using k-means clustering (Sculley, 2010), and images are then quantized over the 5,000 codewords. We compute SURF keypoints for every image in our data set using SimpleCV3 and randomly sample 1% of the keypoints. It is faster and more forgiving than the commonly known SIFT algorithm. Citation Sentence: The keypoints are clustered into 5,000 visual codewords ( centroids ) using k-means clustering ( Sculley , 2010 ) , and images are then quantized over the 5,000 codewords . Context after the citation: All images for a given word are summed together to provide an average representation for the word. We refer to this representation as the SURF modality. While this is a standard, basic BoVW model, each individual codeword on its own may not provide a large degree of semantic information; typically a BoVW representation acts predominantly as a feature space for a classifier, and objects can only be recognize using collections of codewords. To test that similar concepts should share similar visual codewords, we cluster the BoVW representations for all our images into 500 clusters with kmeans clustering, and represent each word as membership over the image clusters, forming the SURF Clusters modality.

Uses

acl_arc_intent_classification:train:383

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: introduction Context before the citation: Another approach for partial parsing was presented by Skut and Brants (1998). The inferences process is cascaded, and a clear improvement was obtained by passing results across cascades. The output of NP and VP chunking was used as an input to grammatical relation inference. Citation Sentence: Another approach for partial parsing was presented by Skut and Brants ( 1998 ) . Context after the citation: Their method is an extension of that of Church (1988) for finding NP's, achieved by extending the feature space to include structural information. Processing goes simultaneously for structures at all levels, from left to right. Since there are no cascades, the structural level of the output is limited by that of the feature set. This paper presents an extension of the algorithm of Argamon et al. (1998, 1999, hereafter MBSL), which handles and exploits compositional structures.

Background

acl_arc_intent_classification:train:384

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: introduction Context before the citation: In knowledge-lean approaches, coreference resolvers employ only morpho-syntactic cues as knowledge sources in the resolution process (e.g., Mitkov (1998), Tetreault (2001)). In the past decade, knowledge-lean approaches have significantly influenced research in noun phrase (NP) coreference resolution — the problem of determining which NPs refer to the same real-world entity in a document. Citation Sentence: In knowledge-lean approaches , coreference resolvers employ only morpho-syntactic cues as knowledge sources in the resolution process ( e.g. , Mitkov ( 1998 ) , Tetreault ( 2001 ) ) . Context after the citation: While these approaches have been reasonably successful (see Mitkov (2002)), Kehler et al. (2004) speculate that deeper linguistic knowledge needs to be made available to resolvers in order to reach the next level of performance. In fact, semantics plays a crucially important role in the resolution of common NPs, allowing us to identify the coreference relation between two lexically dissimilar common nouns (e.g., talks and negotiations) and to eliminate George W. Bush from the list of candidate antecedents of the city, for instance. As a result, researchers have re-adopted the once-popular knowledge-rich approach, investigating a variety of semantic knowledge sources for common noun resolution, such as the semantic relations between two NPs (e.g., Ji et al. (2005)), their semantic similarity as computed using WordNet (e.g., Poesio et al. (2004)) or Wikipedia (Ponzetto and Strube, 2006), and the contextual role played by an NP (see Bean and Riloff (2004)). Another type of semantic knowledge that has been employed by coreference resolvers is the semantic class (SC) of an NP, which can be used to disallow coreference between semantically incompatible NPs.

Background

acl_arc_intent_classification:train:385

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: related work Context before the citation: The application of domain models and deep semantic knowledge to question answering has been explored by a variety of researchers (e.g., Jacquemart and Zweigenbaum 2003, Rinaldi et al. 2004), and was also the focus of recent workshops on question answering in restricted domains at ACL 2004 and AAAI 2005. Patient information is no doubt important to answering clinical questions, and our work could certainly benefit from experiences gained in the PERSIVAL project. Although the system incorporates both a user and a task model, it does not explicitly capture the principles of evidence-based medicine. Citation Sentence: The application of domain models and deep semantic knowledge to question answering has been explored by a variety of researchers ( e.g. , Jacquemart and Zweigenbaum 2003 , Rinaldi et al. 2004 ) , and was also the focus of recent workshops on question answering in restricted domains at ACL 2004 and AAAI 2005 . Context after the citation: Our work contributes to this ongoing discourse by demonstrating a specific application in the domain of clinical medicine. Finally, the evaluation of answers to complex questions remains an open research problem. Although it is clear that measures designed for open-domain factoid questions are not appropriate, the community has not agreed on a methodology that will allow meaningful comparisons of results from different systems. In Sections 9 and 10, we have discussed many of these issues.

Background

acl_arc_intent_classification:train:386

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: experiments Context before the citation: This result is consistent with other works using this model with these features (Andrews et al., 2009; Silberer and Lapata, 2012). The 2D models employing feature norms and association norms do significantly better than the text-only model (two-tailed t-test). Table 1 shows our results for each of our selected models with our compositionality evaluation. Citation Sentence: This result is consistent with other works using this model with these features ( Andrews et al. , 2009 ; Silberer and Lapata , 2012 ) . Context after the citation: We also see that the SURF visual words are able to provide notable, albeit not significant, improvements over the text-only modality. This confirms that the low-level BoVW features do carry semantic information, and are useful to consider individually. The GIST vectors, on the other hand, perform almost exactly the same as the text-only model. These features, which are usually more useful for comparing overall image likeness than object likeness, do not individually contain semantic information useful for compositionality prediction.

CompareOrContrast

acl_arc_intent_classification:train:387

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: None Context before the citation: Cases of intracategorial synonymy are relatively straigthtforward as several electronic synonym dictionnaries for french are available (Ploux, 1997). Depending on the type of paraphrastic means involved, constructing a paraphrastic set (the set of all lexical items related by a paraphrastic link be it parallel, shuffling or definitional) is more or less easy as resources for that specific means may or may not be readily available. Constructing paraphrastic sets. Citation Sentence: Cases of intracategorial synonymy are relatively straigthtforward as several electronic synonym dictionnaries for french are available ( Ploux , 1997 ) . Context after the citation: Multi word expressions however remain a problem as they are often not or only partially included in such dictionnaries. For these or for a specific domain, basic synonymic dictionaries can be complemented using learning methods based on distributional similarity (Pereira et al., 1993; Lin, 1998). techniques. For intercategorial synonymy involving a derivational morphology link, some resources are available which however are only partial in that they only store morphological families that is, sets of items that are morphologically related.

Background

acl_arc_intent_classification:train:388

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: related work Context before the citation: The feature of head word trigger which we apply to the log-linear model is motivated by the trigger-based approach (Hasan and Ney, 2009). Besides, our system complexity is not increased because no additional language model is introduced. The basic difference of our method from (Shen et al., 2008) is that we keep rules that both sides should be relaxed-wellformed dependency structure, not just the target side. Citation Sentence: The feature of head word trigger which we apply to the log-linear model is motivated by the trigger-based approach ( Hasan and Ney , 2009 ) . Context after the citation: Hasan and Ney (2009) introduced a second word to trigger the target word without considering any linguistic information. Furthermore, since the second word can come from any part of the sentence, there may be a prohibitively large number of parameters involved. Besides, He et al. (2008) built a maximum entropy model which combines rich context information for selecting translation rules during decoding. However, as the size of the corpus increases, the maximum entropy model will become larger.

Motivation

acl_arc_intent_classification:train:389

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: conclusion Context before the citation: There has been some controversy, at least for simple stemmers (Lovins, 1968; Porter, 1980), about the effectiveness of morphological analysis for document retrieval (Harman, 1991; Krovetz, 1993; Hull, 1996). Citation Sentence: There has been some controversy , at least for simple stemmers ( Lovins , 1968 ; Porter , 1980 ) , about the effectiveness of morphological analysis for document retrieval ( Harman , 1991 ; Krovetz , 1993 ; Hull , 1996 ) . Context after the citation: The key for quality improvement seems to be rooted mainly in the presence or absence of some form of dictionary. Empirical evidence has been brought forward that inflectional and/or derivational stemmers augmented by dictionaries indeed perform substantially better than those without access to such lexical repositories (Krovetz, 1993; Kraaij and Pohlmann, 1996; Tzoukermann et al., 1997). This result is particularly valid for natural languages with a rich morphology — both in terms of derivation and (single-word) composition. Document retrieval in these languages suffers from serious performance degradation with the stemmingonly query-term-to-text-word matching paradigm.

Background

acl_arc_intent_classification:train:39

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: related work Context before the citation: Other work on modeling the meanings of verbs using video recognition has also begun showing great promise (Mathe et al., 2008; Regneri et al., 2013). norms. More recently, Silberer et al. (2013) show that visual attribute classifiers, which have been immensely successful in object recognition (Farhadi et al., 2009), act as excellent substitutes for feature Citation Sentence: Other work on modeling the meanings of verbs using video recognition has also begun showing great promise ( Mathe et al. , 2008 ; Regneri et al. , 2013 ) . Context after the citation: The Computer Vision community has also benefited greatly from efforts to unify the two modalities. To name a few examples, Rohrbach et al. (2010) and Socher et al. (2013) show how semantic information from text can be used to improve zero-shot classification (i.e., classifying never-before-seen objects), and Motwani and Mooney (2012) show that verb clusters can be used to improve activity recognition in videos.

Background

acl_arc_intent_classification:train:390

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: experiments Context before the citation: based parsing algorithms with an arc-factored parameterization (McDonald et al., 2005). • Graph-based: An implementation of graph- All feature conjunctions are included. Citation Sentence: based parsing algorithms with an arc-factored parameterization ( McDonald et al. , 2005 ) . Context after the citation: We use the non-projective k-best MST algorithm to generate k-best lists (Hall, 2007), where k = 8 for the experiments in this paper. The graphbased parser features used in the experiments in this paper are defined over a word, wi at position i; the head of this word wρ(i) where ρ(i) provides the index of the head word; and partof-speech tags of these words ti. We use the following set of features similar to McDonald et al. (2005):

Uses

acl_arc_intent_classification:train:391

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: None Context before the citation: No attempt has been made to map any closed class entries from LDOCE, as a 3,000 word lexicon containing most closed class items has been developed independently by one of the groups collaborating with us to develop the general purpose morphological and syntactic analyser (see the Introduction and Russell et al., 1986). However, the LDOCE coding of verbs is more comprehensive than elsewhere, so verbs are the obvious place to start in an evaluation of the usefulness of the coding system. Extending the system to handle nouns, adjectives and adverbs would present no problems of principle. Citation Sentence: No attempt has been made to map any closed class entries from LDOCE , as a 3,000 word lexicon containing most closed class items has been developed independently by one of the groups collaborating with us to develop the general purpose morphological and syntactic analyser ( see the Introduction and Russell et al. , 1986 ) . Context after the citation: Initially the transformation of the LDOCE codes was performed on a code-by-code basis, within a code field associated with each individual word sense. This approach is adequate if all that is required is an indication of the subcategorisation frames relevant to any particular sense. In the main, the code numbers determine a unique subcategorisation. Thus the entries can be used to select the appropriate VP rules from the grammar (assuming a GPSG-style approach to subcategorisation) Computational Linguistics, Volume 13, Numbers 3-4, July-December 1987 209 Bran Boguraev and Ted Briscoe Large Lexicons for Natural Language Processing and the relevant word senses of a verb in a particular grammatical context can be determined.

Background

acl_arc_intent_classification:train:392

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: introduction Context before the citation: In this paper we focus on the exploitation of the LDOCE grammar coding system; Alshawi et al. (1985) and Alshawi (1987) describe further research in Cambridge utilising different types of information available in LDOCE. (Michiels (1982) contains further description and discussion of LDOCE.) Most prominent among these are the rich grammatical subcategorisations of the 60,000 entries, the large amount of information concerning phrasal verbs, noun compounds and idioms, the individual subject, collocational and semantic codes for the entries and the consistent use of a controlled 'core' vocabulary in defining the words throughout the dictionary. Citation Sentence: In this paper we focus on the exploitation of the LDOCE grammar coding system ; Alshawi et al. ( 1985 ) and Alshawi ( 1987 ) describe further research in Cambridge utilising different types of information available in LDOCE . Context after the citation: The information available in the dictionary is both very rich and diverse, but also typically only semiformalised, as it is intended for human, rather than machine, interpetation. As a consequence the programs we are developing, both to restructure and to exploit this information, need to undergo constant revision as they are being used. The system we describe is not intended for off-line use, where one might attempt to derive, completely automatically, a lexicon for natural language analysis. Rather than trying to batch process the electronic source, lexicon development from the LDOCE tape is more incremental and interactive.

Background

acl_arc_intent_classification:train:393

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: None Context before the citation: Thus, the second class of SBD systems employs machine learning techniques such as decision tree classifiers (Riley 1989), neural networks (Palmer and Hearst 1994), and maximum-entropy modeling (Reynar and Ratnaparkhi 1997). Automatically trainable software is generally seen as a way of producing systems that are quickly retrainable for a new corpus, for a new domain, or even for another language. Another well-acknowledged shortcoming of rule-based systems is that such systems are usually closely tailored to a particular corpus or sublanguage and are not easily portable across domains. Citation Sentence: Thus , the second class of SBD systems employs machine learning techniques such as decision tree classifiers ( Riley 1989 ) , neural networks ( Palmer and Hearst 1994 ) , and maximum-entropy modeling ( Reynar and Ratnaparkhi 1997 ) . Context after the citation: Machine learning systems treat the SBD task as a classification problem, using features such as word spelling, capitalization, suffix, and word class found in the local context of a potential sentence-terminating punctuation sign. Although training of such systems is completely automatic, the majority of machine learning approaches to the SBD task require labeled examples for training. This implies an investment in the data annotation phase.

Background

acl_arc_intent_classification:train:394

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: None Context before the citation: We see no good reason, however, why such text spans should necessarily be sentences, since the majority of tagging paradigms (e.g., Hidden Markov Model [HMM] [Kupiec 1992], Brill’s [Brill 1995a], and MaxEnt [Ratnaparkhi 1996]) do not attempt to parse an entire sentence and operate only in the local window of two to three tokens. This requires resolving sentence boundaries before tagging. tagger operates on text spans that form a sentence. Citation Sentence: We see no good reason , however , why such text spans should necessarily be sentences , since the majority of tagging paradigms ( e.g. , Hidden Markov Model [ HMM ] [ Kupiec 1992 ] , Brill 's [ Brill 1995a ] , and MaxEnt [ Ratnaparkhi 1996 ] ) do not attempt to parse an entire sentence and operate only in the local window of two to three tokens . Context after the citation: The only reason why taggers traditionally operate on the sentence level is that a sentence naturally represents a text span in which POS information does not depend on the previous and following history. This issue can be also addressed by breaking the text into short text spans at positions where the previous tagging history does not affect current decisions. For instance, a bigram tagger operates within a window of two tokens, and thus a sequence of word tokens can be terminated at an unambiguous word token, since this unambiguous word token will be the only history used in tagging of the next token. At the same time since this token is unambiguous, it is not affected by the history.

CompareOrContrast

acl_arc_intent_classification:train:395

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: introduction Context before the citation: Similarly, (Barzilay and Lee, 2003) and (Shinyanma et al., 2002) learn sentence level paraphrase templates from a corpus of news articles stemming from different news source. For instance, (Lin and Pantel, 2001) acquire two-argument templates (inference rules) from corpora using an extended version of the distributional analysis in which paths in dependency trees that have similar arguments are taken to be close in meaning. Because of the large, open domain corpora these systems deal with, coverage and robustness are key issues and much on the work on paraphrases in that domain is based on automatic learning techniques. Citation Sentence: Similarly , ( Barzilay and Lee , 2003 ) and ( Shinyanma et al. , 2002 ) learn sentence level paraphrase templates from a corpus of news articles stemming from different news source . Context after the citation: And (Glickman and Dagan, 2003) use clustering and similarity measures to identify similar contexts in a single corpus and extract verbal paraphrases from these contexts. Such machine learning approaches have known pros and cons. On the one hand, they produce large scale resources at little man labour cost. On the other hand, the degree of descriptive abstraction offered by the list of inference or paraphrase rules they output is low.

Background

acl_arc_intent_classification:train:396

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: conclusion Context before the citation: In future work we plan to experiment with richer representations, e.g. including long-range n-grams (Rosenfeld, 1996), class n-grams (Brown et al., 1992), grammatical features (Amaya and Benedy, 2001), etc'. The sentence representation we chose for this work is rather simple, and was intended primarily to demonstrate the efficacy of our approach. In our work, the 'neighborhood' is determined automatically and dynamically as learning proceeds, according to the capabilities of the classifiers used. Citation Sentence: In future work we plan to experiment with richer representations , e.g. including long-range n-grams ( Rosenfeld , 1996 ) , class n-grams ( Brown et al. , 1992 ) , grammatical features ( Amaya and Benedy , 2001 ) , etc ' . Context after the citation: The main computational bottleneck in our approach is the generation of negative samples from the current model. Rejection sampling allowed us to use computationally intensive classifiers as our features by reducing the number of classifications that had to be performed during the sampling process. However, if the boosted model strays too far from the baseline P0, these savings will be negated by the very large sentence rejection probabilities that will ensue. This is likely to be the case when richer representations as suggested above are used, necessitating a return to Gibbs sampling.

FutureWork

acl_arc_intent_classification:train:397

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: related work Context before the citation: Furthermore, we demonstrate that our results carry over successfully to another parser, the Easy-First Parser (Goldberg and Elhadad 2010) (Section 6). Our work is the first to show gains using agreement in MaltParser and in Arabic dependency parsing, and the first to use functional features for this task. Previous work with MaltParser in Russian, Turkish, and Hindi showed gains with CASE but not with agreement features (Eryigit, Nivre, and Oflazer 2008; Nivre, Boguslavsky, and Iomdin 2008; Nivre 2009). Citation Sentence: Furthermore , we demonstrate that our results carry over successfully to another parser , the Easy-First Parser ( Goldberg and Elhadad 2010 ) ( Section 6 ) . Context after the citation: Hohensee and Bender (2012) have conducted a study on dependency parsing for 21 languages using features that encode whether the values for certain attributes are equal or not for a node and its governor. These features are potentially powerful, because they generalize to the very notion of agreement, away from the specific values of the attributes on which agreement occurs.9 We expect this kind of feature to yield lower gains for Arabic, unless: • one uses functional feature values (such as those used here for the first time in Arabic NLP), • one uses yet another representation level to account for the otherwise non-identity agreement patterns of irrational plurals, • one handles the loss of overt number agreement in constructions such as VS (where the verb precedes its subject), and • one adequately represents the otherwise “inverse” number agreement (a phenomenon common to other Semitic languages, such as Hebrew, too). 4.

Uses

acl_arc_intent_classification:train:398

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: introduction Context before the citation: For instance, relating "they" to "apples" in the sentence (cfXXX Haugeland 1985 p. 195; Zadrozny 1987a): We bought the boys apples because they were so cheap It should not come as a surprise that we can now use this apparatus for text/discourse analysis; after all, many natural language inferences are based on defaults, and quite often they can be reduced to choosing most plausible interpretations of predicates. This semantics was constructed (Zadrozny 1987a, 1987b) as a formal framework for default and commonsense reasoning. Citation Sentence: For instance , relating `` they '' to `` apples '' in the sentence ( cfXXX Haugeland 1985 p. 195 ; Zadrozny 1987a ) : We bought the boys apples because they were so cheap Context after the citation: can be an example of such a most plausible choice. The main ideas of the three-level semantics can be stated as follows: 1. Reasoning takes place in a three-level structure consisting of an object level, a referential level, and a metalevel.

Background

acl_arc_intent_classification:train:399

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: None Context before the citation: Briscoe and Carroll (1997) report on manually analyzing an open-class vocabulary of 35,000 head words for predicate subcategorization information and comparing the results against the subcategorization details in COMLEX. As a generalization, Briscoe (2001) notes that lexicons such as COMLEX tend to demonstrate high precision but low recall. which is bound to be less certain than the assignment of frames based entirely on existing examples. Citation Sentence: Briscoe and Carroll ( 1997 ) report on manually analyzing an open-class vocabulary of 35,000 head words for predicate subcategorization information and comparing the results against the subcategorization details in COMLEX . Context after the citation: Precision was quite high (95%), but recall was low (84%). This has an effect on both the precision and recall scores of our system against COMLEX. In order to ascertain the effect of using COMLEX as a gold standard for our induced lexicon, we carried out some more-detailed error analysis, the results of which are summarized in Table 26. We randomly selected 80 false negatives (fn) and 80 false positives (fp) across a range of active frame types containing prepositional and particle detail taken from Penn-III and manually examined them in order to classify them as “correct” or “incorrect.”

CompareOrContrast

acl_arc_intent_classification:train:4

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: method Context before the citation: in history-based models (Black et al., 1993), the probability estimate for each derivation decision di is conditioned on the previous derivation decisions d1,..., d,_1, which is called the derivation history at step i. The probability of the input sentence is a constant across all the candidate derivations, so we only need to find the most probable derivation. structure trees to our derivations, the probability of a derivation P(di,..., dm) is equal to the joint probability of the derivation's tree and the input sentence. Citation Sentence: in history-based models ( Black et al. , 1993 ) , the probability estimate for each derivation decision di is conditioned on the previous derivation decisions d1 , ... , d , _ 1 , which is called the derivation history at step i . Context after the citation: This allows us to use the chain rule for conditional probabilities to derive the probability of the entire derivation as the multiplication of the probabilities for each of its decisions. The probabilities P(dild1,..., d1)' are the parameters of the parser's probability model. To define the parameters di_i) we need to choose the ordering of the decisions in a derivation, such as a top-down or shift-reduce ordering. The ordering which we use here is that of a form of left-corner parser (Rosenkrantz and Lewis, 1970).

Uses

acl_arc_intent_classification:train:40

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: None Context before the citation: We follow our previous work (Dickinson et al., 2010) in our feature choices, using a fiveword window that includes the target stem and two words on either side for context (see also Tetreault and Chodorow, 2008). In selecting features for Korean, we have to account for relatively free word order (Chung et al., 2010). For actual system performance, we evaluate both steps. Citation Sentence: We follow our previous work ( Dickinson et al. , 2010 ) in our feature choices , using a fiveword window that includes the target stem and two words on either side for context ( see also Tetreault and Chodorow , 2008 ) . Context after the citation: Each word is broken down into: stem, affixes, stem POS, and affixes POS. We also have features for the preceding and following noun and verb, thereby approximating relevant selectional properties. Although these are relatively shallow features, they provide enough lexical and grammatical context to help select better or worse training data (section 3) and to provide a basis for a preliminary system (section 4).

Extends

acl_arc_intent_classification:train:400

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: introduction Context before the citation: Adjectives, more than other categories, are a striking example of regular polysemy since they are able to take on different meanings depending on their context, viz., the noun or noun class they modify (see Pustejovsky (1995) and the references therein). Much recent work in lexical semantics has been concerned with accounting for regular polysemy, i.e., the regular and predictable sense alternations certain classes of words are subject to. Citation Sentence: Adjectives , more than other categories , are a striking example of regular polysemy since they are able to take on different meanings depending on their context , viz. , the noun or noun class they modify ( see Pustejovsky ( 1995 ) and the references therein ) . Context after the citation: The adjective fast in (1) receives different interpretations when modifying the nouns programmer, plane and scientist. A fast programmer is typically a programmer who programs quickly, a fast plane is typically a plane that flies quickly, a fast scientist can be a scientist who publishes papers quickly, who performs experiments quickly, who observes something quickly, who reasons, thinks, or runs quickly. Interestingly, adjectives like fast are ambiguous across and within the nouns they modify. A fast plane is not only a plane that flies quickly, but also a plane that lands, takes off, turns, or travels quickly.

Background

acl_arc_intent_classification:train:401

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: None Context before the citation: According to Dalrymple (2001), LFG assumes the following universally available inventory of grammatical functions: SUBJ(ect), OBJ(ect), OBJe, COMP, XCOMP, OBL(ique)e, ADJ(unct), XADJ. The argument list can be empty, as in the PRED value for judge in Figure 1. In Figure 1 the verb FOCUS requires a subject and an oblique object introduced by the preposition on: FOCUS((r SUBJ)(r OBLon)). Citation Sentence: According to Dalrymple ( 2001 ) , LFG assumes the following universally available inventory of grammatical functions : SUBJ ( ect ) , OBJ ( ect ) , OBJe , COMP , XCOMP , OBL ( ique ) e , ADJ ( unct ) , XADJ . Context after the citation: OBJe and OBLe represent families of grammatical functions indexed by their semantic role, represented by the theta subscript. This list of grammatical functions is divided into governable (subcategorizable) grammatical functions (arguments) and nongovernable (nonsubcategorizable) grammatical functions (modifiers/adjuncts), as summarized in Table 1. 2 LFGs may also involve morphological and semantic levels of representation. Sample LFG rules and lexical entries.

Background

acl_arc_intent_classification:train:402

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: introduction Context before the citation: But their importance has grown far beyond machine translation: for instance, transferring annotations between languages (Yarowsky and Ngai 2001; Hwa et al. 2005; Ganchev, Gillenwater, and Taskar 2009); discovery of paraphrases (Bannard and Callison-Burch 2005); and joint unsupervised POS and parser induction across languages (Snyder and Barzilay 2008). MT system combination (Matusov, Ueffing, and Ney 2006). Word alignments are used primarily for extracting minimal translation units for machine translation (MT) (e.g., phrases [Koehn, Och, and Marcu 2003] and rules [Galley et al. 2004; Chiang et al. 2005]) as well as for Citation Sentence: But their importance has grown far beyond machine translation : for instance , transferring annotations between languages ( Yarowsky and Ngai 2001 ; Hwa et al. 2005 ; Ganchev , Gillenwater , and Taskar 2009 ) ; discovery of paraphrases ( Bannard and Callison-Burch 2005 ) ; and joint unsupervised POS and parser induction across languages ( Snyder and Barzilay 2008 ) . Context after the citation: IBM Models 1 and 2 and the HMM are simple and tractable probabilistic models, which produce the target sentence one target word at a time by choosing a source word and generating its translation. IBM Models 3, 4, and 5 attempt to capture fertility (the tendency of each source word to generate several target words), resulting in probabilistically deficient, intractable models that require local heuristic search and are difficult to implement and extend. Many researchers use the GIZA++ software package (Och and Ney 2003) as a black box, selecting IBM Model 4 as a compromise between alignment quality and efficiency. All of the models are asymmetric (switching target and source languages produces drastically different results) and the simpler models (IBM Models 1, 2, and HMM) do not enforce bijectivity (the majority of words translating as a single word).

Motivation

acl_arc_intent_classification:train:403

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: introduction Context before the citation: 4 This interpretation of the signature is sometimes referred to as closed world (Gerdemann and King 1994; Gerdemann 1995). To avoid confusion, we will only use the terminology introduced in the text. Types are also referred to as sorts, appropriateness conditions as feature declarations, and features as attributes. Citation Sentence: 4 This interpretation of the signature is sometimes referred to as closed world ( Gerdemann and King 1994 ; Gerdemann 1995 ) . Context after the citation: 5 An in-depth discussion including a comparison of both approaches is provided in Calcagno, Meurers, and Pollard (in preparation). 6 The Partial-VP Topicalization Lexical Rule proposed by Hinrichs and Nakazawa (1994, 10) is a linguistic example. The in-specification of this lexical rule makes use of an append relation to constrain the valence attribute of the auxiliaries serving as its input. In the lexicon, however, the complements of an auxiliary are uninstantiated because it raises the arguments of its verbal complement.

Background

acl_arc_intent_classification:train:404

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: method Context before the citation: Our training examples are similar to the data created for pseudodisambiguation, the usual evaluation task for SP models (Erk, 2007; Keller and Lapata, 2003; Rooth et al., 1999). Similarity-smoothed models can make use of the regularities across similar verbs, but not the finergrained stringand token-based features. This classifier can score any noun as a plausible argument of eat if indicative features are present; MI can only assign high plausibility to observed (eat,n) pairs. Citation Sentence: Our training examples are similar to the data created for pseudodisambiguation , the usual evaluation task for SP models ( Erk , 2007 ; Keller and Lapata , 2003 ; Rooth et al. , 1999 ) . Context after the citation: This data consists of triples (v, n, n′) where v, n is a predicateargument pair observed in the corpus and v, n′ has not been observed. The models score correctly if they rank observed (and thus plausible) arguments above corresponding unobserved (and thus likely implausible) ones. We refer to this as Pairwise Disambiguation. Unlike this task, we classify each predicate-argument pair independently as plausible/implausible.

CompareOrContrast

acl_arc_intent_classification:train:405

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: None Context before the citation: There have already been several attempts to develop distributed NLP systems for dialogue systems (Bayer et al., 2001) and speech recognition (Hacioglu and Pellom, 2003). This standardisation of remote procedures is very exciting from a software engineering viewpoint since it allows systems to be totally distributed. Systems can automatically discover and communicate with web services that provide the functionality they require by querying databases of standardised descriptions of services with WSDL and UDDI. Citation Sentence: There have already been several attempts to develop distributed NLP systems for dialogue systems ( Bayer et al. , 2001 ) and speech recognition ( Hacioglu and Pellom , 2003 ) . Context after the citation: Web services will allow components developed by different researchers in different locations to be composed to build larger systems. Because web services are of great commercial interest they are already being supported strongly by many programming languages. For instance, web services can be accessed with very little code in Java, Python, Perl, C, C++ and Prolog. This allows us to provide NLP services to many systems that we could not otherwise support using a single interface definition.

Background

acl_arc_intent_classification:train:406

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: conclusion Context before the citation: For instance, implementing an efficient version of the MXPOST POS tagger (Ratnaparkhi, 1996) will simply involve composing and configuring the appropriate text file reading component, with the sequential tagging component, the collection of feature extraction components and the maximum entropy model component. The Generative Programming approach to NLP infrastructure development will allow tools such as sentence boundary detectors, POS taggers, chunkers and named entity recognisers to be rapidly composed from many elemental components. Citation Sentence: For instance , implementing an efficient version of the MXPOST POS tagger ( Ratnaparkhi , 1996 ) will simply involve composing and configuring the appropriate text file reading component , with the sequential tagging component , the collection of feature extraction components and the maximum entropy model component . Context after the citation: The individual components will provide state of the art accuracy and be highly optimised for both time and space efficiency. A key design feature of this infrastructure is that components share a common representation for text and annotations so there is no time spent reading/writing formatted data (e.g. XML) between stages. To make the composition and configuration process easier we have implemented a Python scripting interface, which means that anyone can construct efficient new tools, without the need for much programming experience or a compiler. The development of a graphical user interface on top of the infrastructure will further ease the development cycle.

FutureWork

acl_arc_intent_classification:train:407

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: related work Context before the citation: cue word and name the first (or several) associated words that come to mind (e.g., Nelson et al. (2004)), and feature norms, where subjects are given a cue word and asked to describe typical properties of the cue concept (e.g., McRae et al. (2005)). 1http://stephenroller.com/research/ emnlp13 Within the latter category, the two most common representations have been association norms, where subjects are given a Citation Sentence: cue word and name the first ( or several ) associated words that come to mind ( e.g. , Nelson et al. ( 2004 ) ) , and feature norms , where subjects are given a cue word and asked to describe typical properties of the cue concept ( e.g. , McRae et al. ( 2005 ) ) . Context after the citation: Griffiths et al. (2007) helped pave the path for cognitive-linguistic multimodal research, showing that Latent Dirichlet Allocation outperformed Latent Semantic Analysis (Deerwester et al., 1990) in the prediction of association norms. Andrews et al. (2009) furthered this work by showing that a bimodal topic model, consisting of both text and feature norms, outperformed models using only one modality on the prediction of association norms, word substitution errors, and semantic interference tasks. In a similar vein, Steyvers (2010) showed that a different feature-topic model improved predictions on a fill-in-the-blank task. Johns and Jones (2012) take an entirely different approach by showing that one can successfully infer held out feature norms from weighted mixtures based on textual similarity.

Background

acl_arc_intent_classification:train:408

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: introduction Context before the citation: Hirschberg and Litman (1987) and Litman and Hirschberg (1990) also examine the relation between discourse and prosodic phrasing. To our knowledge, no work has explicitly explored the relation between the length of a constituent and its status in the discourse. . Citation Sentence: Hirschberg and Litman ( 1987 ) and Litman and Hirschberg ( 1990 ) also examine the relation between discourse and prosodic phrasing . Context after the citation: Their work succeeds in distinguishing the use of items like now, so, and well as discourse cues from their denotative lexical use on the basis of a complex combination of pitch accent type and phrasing. The Hirschberg and Litman studies identify a specific discourse distinction that relates to phrasing. These studies are not intended to give a picture of the extent to which discourse relates to phrasing. On the other hand, Bing's work gives a broader picture of the relation between discourse and phrasing, but it deals only with noun phrases.

Background

acl_arc_intent_classification:train:409

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: introduction Context before the citation: The reader is referred to Meurers and Minnen (1996) for a more detailed discussion of our use of constraint propagation.32 We illustrate the result of constraint propagation with our example grammar. This technique closely resembles the off-line constraint propagation technique described by Marriott, Naish, and Lassez (1988). Once we have computed c, we use it to make the extended lexical entry more specific. Citation Sentence: The reader is referred to Meurers and Minnen ( 1996 ) for a more detailed discussion of our use of constraint propagation .32 We illustrate the result of constraint propagation with our example grammar . Context after the citation: Since the running example of this paper was kept small, for expository reasons, by only including features that do get changed by one of the lexical rules (which violates the empirical observation mentioned above), the full set of lexical rules would not provide a good example. Let us therefore assume that only the lexical rules 1 and 2 of Figure 11 are given. We then only obtain seven of the clauses of Figure 22: those calling lex_rule_l or lex_rule2, as well as the unit clauses for q_1, q.2, q_3, and q_7. Applying constraint propagation to the extended lexical entry of Figure 17 yields the result shown in Figure 23.

Background

acl_arc_intent_classification:train:41

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: None Context before the citation: Sarkar and Zeman (2000) evaluate 914 Czech verbs against a custom-made gold standard and record a token recall of 88%. Still, to date this is the largest number of verbs used in any of the evaluations of the systems for English described in Section 3. Their system recognizes 15 frames, and these do not contain details of subcategorizedfor prepositions. Citation Sentence: Sarkar and Zeman ( 2000 ) evaluate 914 Czech verbs against a custom-made gold standard and record a token recall of 88 % . Context after the citation: However, their evaluation does not examine the extracted subcategorization frames but rather the argument–adjunct distinctions posited by their system. The largest lexical evaluation we know of is that of Schulte im Walde (2002b) for German. She evaluates 3,000 German verbs with a token frequency between 10 and 2,000 against the Duden (Dudenredaktion 2001). We will refer to this work and the methods and results presented by Schulte im Walde again in Sections 6.2 and 6.3.

CompareOrContrast

acl_arc_intent_classification:train:410

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: method Context before the citation: We use two measures from Information Retrieval to determine the quality of an automatically generated response: precision and F-score (van Rijsbergen 1979; Salton and McGill 1983). Although this method of assessment is less informative than human-based evaluations, it enables us to evaluate the performance of our system with substantial amounts of data, and produce representative results for a large corpus such as ours. For each of the cross-validation folds, the responses generated for the requests in the test split are compared against the actual responses generated by help-desk operators for these requests. Citation Sentence: We use two measures from Information Retrieval to determine the quality of an automatically generated response : precision and F-score ( van Rijsbergen 1979 ; Salton and McGill 1983 ) . Context after the citation: Precision measures how much of the information in an automatically generated response is correct (i.e., appears in the model response), and F-score measures the overall similarity between the automatically generated response and the model response. F-score is the harmonic mean of precision and recall, which measures how much of the information in the model response appears in the generated response. We consider precision separately because it does not penalize missing information, enabling us to better assess our sentence-based methods.

Uses

acl_arc_intent_classification:train:411

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: None Context before the citation: The automation of help-desk responses has been previously tackled using mainly knowledge-intensive paradigms, such as expert systems (Barr and Tessler 1995) and case-based reasoning (Watson 1997). Citation Sentence: The automation of help-desk responses has been previously tackled using mainly knowledge-intensive paradigms , such as expert systems ( Barr and Tessler 1995 ) and case-based reasoning ( Watson 1997 ) . Context after the citation: Such technologies require significant human input, and are difficult to create and maintain (Delic and Lahaix 1998). In contrast, the techniques examined in this article are corpus-based and data-driven. The process of composing a planned response for a new request is informed by probabilistic and lexical properties of the requests and responses in the corpus. There are very few reported attempts at corpus-based automation of help-desk responses (Carmel, Shtalhaim, and Soffer 2000; Lapalme and Kosseim 2003; Bickel and Scheffer 2004; Malik, Subramaniam, and Kaushik 2007).

CompareOrContrast

acl_arc_intent_classification:train:412

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: introduction Context before the citation: Xue and Palmer (2004) did very encouraging work on the feature calibration of semantic role labeling. So the hierarchical system in their paper performs a little worse than the traditional SRL systems, although it is more efficient. However, without considerations on how to utilize the characteristics of linguistically similar semantic roles, the purpose of the hierarchical system is to simplify the classification process to make it less time consuming. Citation Sentence: Xue and Palmer ( 2004 ) did very encouraging work on the feature calibration of semantic role labeling . Context after the citation: They found out that different features suited for different sub tasks of SRL, i.e. semantic role identification and classification. For semantic analysis, developing features that capture the right kind of information is crucial. Experiments on Chinese SRL (Xue and Palmer 2005, Xue 2008) reassured these findings. In this paper, we mainly focus on the semantic role classification (SRC) process.

Background

acl_arc_intent_classification:train:413

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: related work Context before the citation: This approach, which uses words that appear in the context of terms to formulate hypotheses on their semantic relatedness (Habert et al., 1996, for example), does not specify the relationship itself. A number of applications have relied on distributional analysis (Harris, 1971) in order to build classes of semantically related terms. Citation Sentence: This approach , which uses words that appear in the context of terms to formulate hypotheses on their semantic relatedness ( Habert et al. , 1996 , for example ) , does not specify the relationship itself . Context after the citation: Hence, synonyms, co-hyponyms, hyperonyms, etc. are not differentiated. More recent work on terminology structuring has focussed on formal similarity to develop hypotheses on the semantic relationships between terms: Daille (2003) uses derivational morphology; Grabar and Zweigenbaum (2002) use, as a starting point, a number of identical characters. Up to now, the focus has been on nouns and adjectives, since these structuring methods have been applied to lists of extracted candidate terms (Habert et al., 1996; Daille, 2003) or to lists of admitted terms (Grabar and Zweigenbaum, 2002). As a consequence, relationships considered have been mostly synonymic or taxonomic, or defined as term variations.

Background

acl_arc_intent_classification:train:414

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: introduction Context before the citation: And (Glickman and Dagan, 2003) use clustering and similarity measures to identify similar contexts in a single corpus and extract verbal paraphrases from these contexts. Similarly, (Barzilay and Lee, 2003) and (Shinyanma et al., 2002) learn sentence level paraphrase templates from a corpus of news articles stemming from different news source. For instance, (Lin and Pantel, 2001) acquire two-argument templates (inference rules) from corpora using an extended version of the distributional analysis in which paths in dependency trees that have similar arguments are taken to be close in meaning. Citation Sentence: And ( Glickman and Dagan , 2003 ) use clustering and similarity measures to identify similar contexts in a single corpus and extract verbal paraphrases from these contexts . Context after the citation: Such machine learning approaches have known pros and cons. On the one hand, they produce large scale resources at little man labour cost. On the other hand, the degree of descriptive abstraction offered by the list of inference or paraphrase rules they output is low. We chose to investigate an alternative research direction by aiming to develop a “paraphrastic grammar” that is, a grammar which captures the paraphrastic relations between linguistic structuress.

Background

acl_arc_intent_classification:train:415

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: introduction Context before the citation: Not having to represent the frame explicitly not only enables the linguist to express only the relevant things, but also allows a more compact representation of lexical rules where explicit framing would require the rules to be split up (Meurers 1994). This idea of preserving properties can be considered an instance of the well-known frame problem in AT (McCarthy and Hayes 1969), and we will therefore refer to the specifications left implicit by the linguist as the frame specification, or simply frame, of a lexical rule. (Pollard and Sag [1994, 3141, following Flickinger [19871). Citation Sentence: Not having to represent the frame explicitly not only enables the linguist to express only the relevant things , but also allows a more compact representation of lexical rules where explicit framing would require the rules to be split up ( Meurers 1994 ) . Context after the citation: One thus needs to distinguish the lexical rule specification provided by the linguist from the fully explicit lexical rule relations integrated into the theory. The formalization of DLRs provided by Meurers (1995) defines a formal lexical rule specification language and provides a semantics for that language in two steps: A rewrite system enriches the lexical rule specification into a fully explicit description of the kind shown in Figure 1. This description can then be given the standard set-theoretical interpretation of King (1989, 1994).' 10 Note that the passivization lexical rule in Figure 2 is only intended to illustrate the mechanism.

Background

acl_arc_intent_classification:train:416

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: related work Context before the citation: There has also been work focused upon determining the political leaning (e.g., “liberal” vs. “conservative”) of a document or author, where most previously-proposed methods make no direct use of relationships between the documents to be classified (the “unlabeled” texts) (Laver et al., 2003; Efron, 2004; Mullen and Malouf, 2006). Politically-oriented text Sentiment analysis has specifically been proposed as a key enabling technology in eRulemaking, allowing the automatic analysis of the opinions that people submit (Shulman et al., 2005; Cardie et al., 2006; Kwon et al., 2006). Citation Sentence: There has also been work focused upon determining the political leaning ( e.g. , `` liberal '' vs. `` conservative '' ) of a document or author , where most previously-proposed methods make no direct use of relationships between the documents to be classified ( the `` unlabeled '' texts ) ( Laver et al. , 2003 ; Efron , 2004 ; Mullen and Malouf , 2006 ) . Context after the citation: An exception is Grefenstette et al. (2004), who experimented with determining the political orientation of websites essentially by classifying the concatenation of all the documents found on that site. Others have applied the NLP technologies of near-duplicate detection and topic-based text categorization to politically oriented text (Yang and Callan, 2005; Purpura and Hillard, 2006). Detecting agreement We used a simple method to learn to identify cross-speaker references indicating agreement. More sophisticated approaches have been proposed (Hillard et al., 2003), including an extension that, in an interesting reversal of our problem, makes use of sentimentpolarity indicators within speech segments (Galley et al., 2004).

Background

acl_arc_intent_classification:train:417

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: introduction Context before the citation: Other similar approaches include those of Cicekli and G¨uvenir (1996), McTait and Trujillo (1999), Carl (1999), and Brown (2000), inter alia. Watanabe (1993) combines lexical and dependency mappings to form his generalizations. Kaji, Kida, and Morimoto (1992) identify translationally equivalent phrasal segments and replace such equivalents with variables to generate a set of translation patterns. Citation Sentence: Other similar approaches include those of Cicekli and G ¨ uvenir ( 1996 ) , McTait and Trujillo ( 1999 ) , Carl ( 1999 ) , and Brown ( 2000 ) , inter alia . Context after the citation: In our system, in some cases the smallest chunk obtainable via the marker-based segmentation process may be something like (27): (27) <DET> the good man: le bon homme In such cases, if our system were confronted with a good man, it would not be able to translate such a phrase, assuming this to be missing from the marker lexicon. Accordingly, we convert examples such as (27) into their generalized equivalents, as in (28): (28) <DET> good man: bon homme That is, where Block (2000) substitutes variables for various words in his templates, we replace certain lexical items with their marker tag. Given that examples such as ’‘<DET> a : un” are likely to exist in the word-level lexicon, they may be inserted at the point indicated by the marker tag to form the correct translation un bon homme. We thus cluster on marker words to improve the coverage of our system (see Section 5 for results that show exactly how clustering on marker words helps); others (notably Brown [2000, 2003]) use clustering techniques to determine equivalence classes of individual words that can occur in the same context, and in so doing derive translation templates from individual translation examples.

Background

acl_arc_intent_classification:train:418

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: conclusion Context before the citation: To sum up, this work has been carried out to automatically classify Arabic documents using the NB algorithm, with the use of a different data set, a different number of categories, and a different root extraction algorithm from those used in (Yahyaoui, 2001). Citation Sentence: To sum up , this work has been carried out to automatically classify Arabic documents using the NB algorithm , with the use of a different data set , a different number of categories , and a different root extraction algorithm from those used in ( Yahyaoui , 2001 ) . Context after the citation: In this work, the average accuracy over all categories is: 68.78% in cross validation and 62% in evaluation set experiments. The corresponding performances in (Yahyaoui, 2001) are 75.6% and 50%, respectively. Thus, the overall performance (including cross validation and evaluation set experiments) in this work is comparable to that in (Yahyaoui, 2001). This offers some indication that the performance of NB algorithm in classifying Arabic documents is not sensitive to the Arabic root extraction algorithm.

CompareOrContrast

acl_arc_intent_classification:train:419

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: introduction Context before the citation: Such tools make it easy to run most current approaches to statistical markup, chunking, normalization, segmentation, alignment, and noisy-channel decoding,' including classic models for speech recognition (Pereira and Riley, 1997) and machine translation (Knight and Al-Onaizan, 1998). The availability of toolkits for this weighted case (Mohri et al., 1998; van Noord and Gerdemann, 2001) promises to unify much of statistical NLP. An artificial example will appear in §2. Citation Sentence: Such tools make it easy to run most current approaches to statistical markup , chunking , normalization , segmentation , alignment , and noisy-channel decoding , ' including classic models for speech recognition ( Pereira and Riley , 1997 ) and machine translation ( Knight and Al-Onaizan , 1998 ) . Context after the citation: Moreover, once the models are expressed in the finitestate framework, it is easy to use operators to tweak them, to apply them to speech lattices or other sets, and to combine them with linguistic resources. Unfortunately, there is a stumbling block: Where do the weights come from? After all, statistical models require supervised or unsupervised training. Currently, finite-state practitioners derive weights using exogenous training methods, then patch them onto transducer arcs.

Background

acl_arc_intent_classification:train:42

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: conclusion Context before the citation: Our work builds on earlier research on learning to identify dialogues in which the user experienced poor speech recognizer performance (Litman et al., 1999). The research reported here is the first that we know of to automatically analyze a corpus of logs from a spoken dialogue system for the purpose of learning to predict problematic situations. Even with current accuracy rates, the improved ability to predict problematic dialogues means that it may be possible to field the system without human agent oversight, and we expect to be able to improve these results. Citation Sentence: Our work builds on earlier research on learning to identify dialogues in which the user experienced poor speech recognizer performance ( Litman et al. , 1999 ) . Context after the citation: However, that work was based on a much smaller set of experimental dialogues where the notion of a good or bad dialogue was automatically approximated rather than being labelled by humans. In addition, because that work was based on features synthesized over the entire dialogues, the hypotheses that were learned could not be used for prediction during runtime. We are exploring several ways to improve the performance of and test the problematic dialogue predictor. First, we noted above the extent to which the hand-labelled feature rsuccess improves classifier performance.

Extends

acl_arc_intent_classification:train:420

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: introduction Context before the citation: CCGBank (Hockenmaier and Steedman 2007) is used to train the model. We now give an overview of the training algorithm, which is crucial to both the speed and accuracy of the resulting decoder. We will also investigate the possibility of applying dynamic-programming-style pruning to the chart. Citation Sentence: CCGBank ( Hockenmaier and Steedman 2007 ) is used to train the model . Context after the citation: For each training sentence, the corresponding CCGBank derivation together with all its sub-derivations are treated as gold-standard hypotheses. All other hypotheses that can be constructed from the same bag of words are non-gold hypotheses. From the generation perspective this assumption is too strong, because sentences can have multiple orderings (with multiple derivations) that are both grammatical and fluent. Nevertheless, it is the most feasible choice given the training data available.

Uses

acl_arc_intent_classification:train:421

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: related work Context before the citation: More recent work on terminology structuring has focussed on formal similarity to develop hypotheses on the semantic relationships between terms: Daille (2003) uses derivational morphology; Grabar and Zweigenbaum (2002) use, as a starting point, a number of identical characters. Hence, synonyms, co-hyponyms, hyperonyms, etc. are not differentiated. This approach, which uses words that appear in the context of terms to formulate hypotheses on their semantic relatedness (Habert et al., 1996, for example), does not specify the relationship itself. Citation Sentence: More recent work on terminology structuring has focussed on formal similarity to develop hypotheses on the semantic relationships between terms : Daille ( 2003 ) uses derivational morphology ; Grabar and Zweigenbaum ( 2002 ) use , as a starting point , a number of identical characters . Context after the citation: Up to now, the focus has been on nouns and adjectives, since these structuring methods have been applied to lists of extracted candidate terms (Habert et al., 1996; Daille, 2003) or to lists of admitted terms (Grabar and Zweigenbaum, 2002). As a consequence, relationships considered have been mostly synonymic or taxonomic, or defined as term variations. On the other hand, other work has been carried out in order to acquire collocations. Most of these endeavours have focused on purely statistical acquisition techniques (Church and Hanks, 'However, our interpretation of LFs in this work is much looser, since we admitted verbs that would not be considered to be members of true collocations as Mel'cuk et al. (1984 1999) define them, i.e. groups of lexical units that share a restricted cooccurrence relationship.

Background

acl_arc_intent_classification:train:422

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: related work Context before the citation: Some researchers (Cucerzan, 2007; Nguyen and Cao, 2008) have explored the use of Wikipedia information to improve the disambiguation process. Other representations use the link structure (Malin, 2005) or generate graph representations of the extracted features (Kalashnikov et al., 2007). Nevertheless, the full document text is present in most systems, sometimes as the only feature (Sugiyama and Okumura, 2007) and sometimes in combination with others see for instance (Chen and Martin, 2007; Popescu and Magnini, 2007)-. Citation Sentence: Some researchers ( Cucerzan , 2007 ; Nguyen and Cao , 2008 ) have explored the use of Wikipedia information to improve the disambiguation process . Context after the citation: Wikipedia provides candidate entities that are linked to specific mentions in a text. The obvious limitation of this approach is that only celebrities and historical figures can be identified in this way. These approaches are yet to be applied to the specific task of grouping search results. Biographical features are strongly related to NEs and have also been proposed for this task due to its high precision.

Background

acl_arc_intent_classification:train:423

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: related work Context before the citation: To address this issue, we use a version of the PATB3 training and dev sets manually annotated with functional gender, number, and rationality (Alkuhlani and Habash 2011).18 This is the first resource providing all three features (ElixirFm only provides functional number, and to some extent functional gender). The ElixirFM lexical resource used previously provided functional NUMBER feature values but no functional GENDER values, nor RAT (rationality, or humanness) values. Citation Sentence: To address this issue , we use a version of the PATB3 training and dev sets manually annotated with functional gender , number , and rationality ( Alkuhlani and Habash 2011 ) .18 This is the first resource providing all three features ( ElixirFm only provides functional number , and to some extent functional gender ) . Context after the citation: We conducted experiments with gold features to assess the potential of these features, and with predicted features, obtained from training a simple maximum likelihood estimation classifier on this resource (Alkuhlani and Habash 2012).19 The first part of Table 8 shows that the RAT (rationality) feature is very relevant (in gold), but suffers from low accuracy (no gains in machine-predicted input). The next two parts show the advantages of functional gender and number (denoted with a FN* prefix) over their surface-based counterparts. The fourth part of the table shows the combination of these functional features with the other features that participated in the best combination so far (LMM, the extended DET2, and PERSON); without RAT, this combination is at least as useful as its form-based counterpart, in both gold and predicted input; adding RAT to this combination yields 0.4% (absolute) gain in gold, offering further support to the relevance of the rationality feature, but a slight decrease in predicted input, presumably due to insufficient accuracy again. The last part of the table revalidates the gains achieved with the best controlled feature combination, using CATIBEX—the best performing tag set with predicted input.

Uses

acl_arc_intent_classification:train:424

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: None Context before the citation: One approach to this problem is that taken by the ASCOT project (Akkerman et al., 1985; Akkerman, 1986). This type of error and inconsistency arises because grammatical codes are constructed by hand and no automatic checking procedure is attempted (see Michiels, 1982, for further comment). Presumably this kind of inconsistency arose because one member of the team of lexicographers realised that this form of elision saved more space. Citation Sentence: One approach to this problem is that taken by the ASCOT project ( Akkerman et al. , 1985 ; Akkerman , 1986 ) . Context after the citation: In this project, a new lexicon is being manually derived from LDOCE. The coding system for the new lexicon is a slightly modified and simplified version of the LDOCE scheme, without any loss of generalisation and expressive power. More importantly, the assignment of codes for problematic or erroneously labelled words is being corrected in an attempt to make the resulting lexicon more appropriate for automated analysis. In the medium term this approach, though time consuming, will be of some utility for producing more reliable lexicons for natural language processing.

Background

acl_arc_intent_classification:train:425

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: None Context before the citation: Narrative writings or essays are creative works and they generally treat ownership as authorship, even for the most enthusiastic fellows of free culture (Stallman, 2001). We consider the Creative Commons model as the most suitable one to let each author choose the rights to reserve (Lessig, 2004). non-attributive copyright licence to their work. Citation Sentence: Narrative writings or essays are creative works and they generally treat ownership as authorship , even for the most enthusiastic fellows of free culture ( Stallman , 2001 ) . Context after the citation:

Background

acl_arc_intent_classification:train:426

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: None Context before the citation: McDonald has even argued for extending the model to a large number of components (McDonald 1988), and several systems have indeed added an additional component between the planner and the linguistic component (Meteer 1994; Panaget 1994; Wanner 1994). For example, DIOGENES (Nirenburg et al. 1988), EPICURE (Dale 1989), SPOKESMAN (Meteer 1989), Sibun's work on local organization of text (Sibun 1991), and COMET (Fisher and McKeown 1990) all are organized this way. Much (if not most) work in generation, though, continues to rely on this modular approach for its basic design. Citation Sentence: McDonald has even argued for extending the model to a large number of components ( McDonald 1988 ) , and several systems have indeed added an additional component between the planner and the linguistic component ( Meteer 1994 ; Panaget 1994 ; Wanner 1994 ) . Context after the citation: Reiter describes a pipelined modular approach as a consensus architecture underlying most recent work in generation (Reiter 1994). As this large body of work makes clear, the modular approach has been very useful, simplifying the design of generators and making them more flexible. In fact, in at least one case the &quot;tactical&quot; component of a generator was successfully replaced with a radically different independently designed one (Rubinoff 1986). A modular design,

Background

acl_arc_intent_classification:train:427

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: conclusion Context before the citation: According to current tagger comparisons (van Halteren et al., 1998; Zavrel and Daelemans, 1999), and according to a comparsion of the results presented here with those in (Ratnaparkhi, 1996), the Maximum Entropy framework seems to be the only other approach yielding comparable results to the one presented here. The architecture remains applicable to a large variety of languages. They do so for several other corpora as well. Citation Sentence: According to current tagger comparisons ( van Halteren et al. , 1998 ; Zavrel and Daelemans , 1999 ) , and according to a comparsion of the results presented here with those in ( Ratnaparkhi , 1996 ) , the Maximum Entropy framework seems to be the only other approach yielding comparable results to the one presented here . Context after the citation: It is a very interesting future research topic to determine the advantages of either of these approaches, to find the reason for their high accuracies, and to find a good combination of both. TnT is freely available to universities and related organizations for research purposes (see http://www.coli.uni-sb.derthorstenAnt).

CompareOrContrast

acl_arc_intent_classification:train:428

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: related work Context before the citation: Similar findings have been proposed by Pandharipande (1993) that points out V1 and V2 are paired on the basis of their semantic compatibility, which is subject to syntactic constraints. Bashir (1993) tried to construct a semantic analysis based on “prepared” and “unprepared mind”. Butt (1993) argues CV formations in Hindi and Urdu are either morphological or syntactical and their formation take place at the argument structure. Citation Sentence: Similar findings have been proposed by Pandharipande ( 1993 ) that points out V1 and V2 are paired on the basis of their semantic compatibility , which is subject to syntactic constraints . Context after the citation: Paul (2004) tried to represent Bangla CVs in terms of HPSG formalism. She proposes that the selection of a V2 by a V1 is determined at the semantic level because the two verbs will unify if and only if they are semantically compatible. Since none of the linguistic formalism could satisfactorily explain the unique phenomena of CV formation, we here for the first time drew our attention towards psycholinguistic and neurolinguistic studies to model the processing of verb-verb combinations in the ML and compare these responses with that of the existing models.

Background

acl_arc_intent_classification:train:429

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: None Context before the citation: Such technologies require significant human input, and are difficult to create and maintain (Delic and Lahaix 1998). The automation of help-desk responses has been previously tackled using mainly knowledge-intensive paradigms, such as expert systems (Barr and Tessler 1995) and case-based reasoning (Watson 1997). Citation Sentence: Such technologies require significant human input , and are difficult to create and maintain ( Delic and Lahaix 1998 ) . Context after the citation: In contrast, the techniques examined in this article are corpus-based and data-driven. The process of composing a planned response for a new request is informed by probabilistic and lexical properties of the requests and responses in the corpus. There are very few reported attempts at corpus-based automation of help-desk responses (Carmel, Shtalhaim, and Soffer 2000; Lapalme and Kosseim 2003; Bickel and Scheffer 2004; Malik, Subramaniam, and Kaushik 2007). eResponder, the system developed by Carmel, Shtalhaim, and Soffer (2000), retrieves a list of request–response pairs and presents a ranked list of responses to the user.

Background

acl_arc_intent_classification:train:43

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: related work Context before the citation: The first lexical substitution method was proposed by Chapman and Davida (1997). The simplest and most straightforward subliminal modification of text is to substitute selected words with their synonyms. Citation Sentence: The first lexical substitution method was proposed by Chapman and Davida ( 1997 ) . Context after the citation: Later works, such as Atallah et al. (2001a), Bolshakov (2004), Taskiran et al. (2006) and Topkara et al. (2006b), further made use of part-ofspeech taggers and electronic dictionaries, such as WordNet and VerbNet, to increase the robustness of the method. Taskiran et al. (2006) attempt to use context by prioritizing the alternatives using an ngram language model; that is, rather than randomly choose an option from the synonym set, the system relies on the language model to select the synonym. Topkara et al. (2005) and Topkara et al. (2006b) report an average embedding capacity of 0.67 bits per sentence for the synonym substitution method.

Background

acl_arc_intent_classification:train:430

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: None Context before the citation: This can be a hazardous affair, since vague expressions tend to be interpreted in different ways by different people (Toogood 1980), sometimes in stark contrast with the intention of the speaker/writer (Berry, Knapp, and Raynor 2002). We shall focus on the more challenging case where the output of the generator is less precise than the input, as is the case in FOG and DYD. Such cases can be modeled by letting NLG systems take vague information (e.g., Rain[Wednesday] = heavy) as their input. Citation Sentence: This can be a hazardous affair , since vague expressions tend to be interpreted in different ways by different people ( Toogood 1980 ) , sometimes in stark contrast with the intention of the speaker/writer ( Berry , Knapp , and Raynor 2002 ) . Context after the citation: We shall therefore focus—unlike earlier computational accounts—on vague descriptions, that is, vague expressions in definite descriptions. Here, the context tends to obliterate the vagueness associated with the adjective. Suppose you enter a vet’s surgery in the company of two dogs: a big one on a leash, and a tiny one in your arms. The vet asks “Who’s the patient?”

Background

acl_arc_intent_classification:train:431

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: None Context before the citation: We see no good reason, however, why such text spans should necessarily be sentences, since the majority of tagging paradigms (e.g., Hidden Markov Model [HMM] [Kupiec 1992], Brill’s [Brill 1995a], and MaxEnt [Ratnaparkhi 1996]) do not attempt to parse an entire sentence and operate only in the local window of two to three tokens. This requires resolving sentence boundaries before tagging. tagger operates on text spans that form a sentence. Citation Sentence: We see no good reason , however , why such text spans should necessarily be sentences , since the majority of tagging paradigms ( e.g. , Hidden Markov Model [ HMM ] [ Kupiec 1992 ] , Brill 's [ Brill 1995a ] , and MaxEnt [ Ratnaparkhi 1996 ] ) do not attempt to parse an entire sentence and operate only in the local window of two to three tokens . Context after the citation: The only reason why taggers traditionally operate on the sentence level is that a sentence naturally represents a text span in which POS information does not depend on the previous and following history. This issue can be also addressed by breaking the text into short text spans at positions where the previous tagging history does not affect current decisions. For instance, a bigram tagger operates within a window of two tokens, and thus a sequence of word tokens can be terminated at an unambiguous word token, since this unambiguous word token will be the only history used in tagging of the next token. At the same time since this token is unambiguous, it is not affected by the history.

CompareOrContrast

acl_arc_intent_classification:train:432

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: introduction Context before the citation: Hermann and Deutsch (1976; also reported in Levelt 1989) show that greater differences are most likely to be chosen, presumably because they are more striking. Suppose, for example, that the KB contains information about height as well as width, then we have inequalities of the forms (a) height > x, (b) height < x, (c) width > x, and (d) width < x. Which of these should come first? Even if comparative properties are at the bottom of the preference order, while stronger inequalities precede weaker ones, the order is not fixed completely. Citation Sentence: Hermann and Deutsch ( 1976 ; also reported in Levelt 1989 ) show that greater differences are most likely to be chosen , presumably because they are more striking . Context after the citation: In experiments involving candles of different heights and widths, if the referent is both the tallest and the fattest candle, subjects tended to say ‘the tall candle’ when the tallest candle is much taller than all others whereas the same candle is only slightly wider than the others; if the reverse is the case, the preference switches to ‘the fat candle.’ Hermann and Deutsch’s findings may be implemented as follows. First, the Values of the different Attributes should be normalized to make them comparable. Second, preference order should be calculated 5 A statement p is logically stronger than q if p has q as a logical consequence (i.e., p �= q), whereas the reverse is not true (i.e., q V p).

Background

acl_arc_intent_classification:train:433

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: None Context before the citation: Nevertheless, recent results show that knowledge-poor methods perform with amazing accuracy (cfXXX (Mitkov, 1998), (Kennedy and Boguraev, 1996) (Kameyama, 1997)). The acquisition of such knowledge is time-consuming, difficult, and error-prone. Traditionally, these techniques have combined extensive syntactic, semantic, and discourse knowledge. Citation Sentence: Nevertheless , recent results show that knowledge-poor methods perform with amazing accuracy ( cfXXX ( Mitkov , 1998 ) , ( Kennedy and Boguraev , 1996 ) ( Kameyama , 1997 ) ) . Context after the citation: For example, CogNIAC (Baldwin, 1997), a system based on seven ordered heuristics, generates high-precision resolution (over 90%) for some cases of pronominal reference. For this research, we used a coreference resolution system ((Harabagiu and Maiorano, 1999)) that implements different sets of heuristics corresponding to various forms of coreference. This system, called COCKTAIL, resolves coreference by exploiting several textual cohesion constraints (e.g. term repetition) combined with lexical and textual coherence cues (e.g. subjects of communication verbs are more likely to refer to the last person mentioned in the text). These constraints are implemented as a set of heuristics ordered by their priority.

Background

acl_arc_intent_classification:train:434

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: None Context before the citation: Notice that it is not possible to use corpus annotation to determine the likelihood of a given property to be chosen, unless we know in advance all of the properties that can be attributed to a given object, as in the case of Jordan's work on the COCONUT domain (Jordan, 2000). Through corpus annotation, we wish to answer the question of what will be the probability of a given piece of information occupying a given syntactic position (a value of type) on the basis of the semantic and pragmatic properties of that information and relevant NP features, for example, whether a certain color attribute should be expressed by means of a prenominal adjective or a prepositional phrase in a definite NP. e.g. prenominal or postnominal, adjectival or as a relative clause. Citation Sentence: Notice that it is not possible to use corpus annotation to determine the likelihood of a given property to be chosen , unless we know in advance all of the properties that can be attributed to a given object , as in the case of Jordan 's work on the COCONUT domain ( Jordan , 2000 ) . Context after the citation: Below we briefly introduce the major values of the three modifier features. Pragm We observed three modifier functions in NPs. Firstly, a modifier may specify properties that uniquely identify the objects or concepts denoted by an NP, i.e. components of the referring part of an NP. We call such modifiers uniq modifiers; most modifiers in generic references are of this type.

Background

acl_arc_intent_classification:train:435

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: None Context before the citation: Some well-known approaches include rule-based models (Brill and Resnik 1994), backed-off models (Collins and Brooks 1995), and a maximumentropy model (Ratnaparkhi 1998). Researchers have proposed many computational models for resolving PPattachment ambiguities. One common source of structural ambiguities arises from syntactic constructs in which a prepositional phrase might be equally likely to modify the verb or the noun preceding it. Citation Sentence: Some well-known approaches include rule-based models ( Brill and Resnik 1994 ) , backed-off models ( Collins and Brooks 1995 ) , and a maximumentropy model ( Ratnaparkhi 1998 ) . Context after the citation: Following the tradition of using learning PPattachment as a way to gain insight into the parsing problem, we first apply sample selection to reduce the amount of annotation used in training a PP-attachment model. We use the Collins-Brooks model as the basic learning algorithm and experiment with several evaluation functions based on the types of predictive criteria described earlier. Our experiments show that the best evaluation function can reduce the number of labeled examples by nearly half without loss of accuracy.

Background

acl_arc_intent_classification:train:436

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: introduction Context before the citation: Other psycholing-uistic studies that confirm the validity of paragraph units can be found in Black and Bower (1979) and Haberlandt et al. (1980). Bond and Hayes found three major formal devices that are used, by readers, to identify a paragraph: (1) the repetition of content words (nouns, verbs, adjectives, adverbs); (2) pronoun reference; and (3) paragraph length, as determined by spatial and/or sentence-count information. These authors take the position that a paragraph is a psychologically real unit of discourse, and, in fact, a formal grammatical unit. Citation Sentence: Other psycholing-uistic studies that confirm the validity of paragraph units can be found in Black and Bower ( 1979 ) and Haberlandt et al. ( 1980 ) . Context after the citation: The textualist approach to paragraph analysis is exemplified by E. J. Crothers. His work is taxonomic, in that he performs detailed descriptive analyses of paragraphs. He lists, classifies, and discusses various types of inference, by which he means, generally, &quot;the linguistic-logical notions of consequent and presupposition&quot; Crothers (1979:112) have collected convincing evidence of the existence of language chunks—real structures, not just orthographic conventions—that are smaller than a discourse, larger than a sentence, generally composed of sentences, and recursive in nature (like sentences). These chunks are sometimes called &quot;episodes,&quot; and sometimes &quot;paragraphs.&quot;

Background

acl_arc_intent_classification:train:437

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: None Context before the citation: Tetreault's contribution features comparative evaluation involving the author's own centering-based pronoun resolution algorithm called the Left-Right Centering algorithm (LRC) as well as three other pronoun resolution methods: Hobbs's naive algorithm (Hobbs 1978), BFP (Brennan, Friedman, and Pollard 1987), and Strube's 5list approach (Strube 1998). In particular, both developer-oriented (e.g., related to the selection of optimal resolution factors) and application-oriented (e.g., related to the requirement of the application, as in the case of information extraction, where a proper name antecedent is needed) evaluation metrics should be considered. He also argues that evaluation of anaphora resolution systems should take into account several factors beyond simple accuracy of resolution. Citation Sentence: Tetreault 's contribution features comparative evaluation involving the author 's own centering-based pronoun resolution algorithm called the Left-Right Centering algorithm ( LRC ) as well as three other pronoun resolution methods : Hobbs 's naive algorithm ( Hobbs 1978 ) , BFP ( Brennan , Friedman , and Pollard 1987 ) , and Strube 's 5list approach ( Strube 1998 ) . Context after the citation: The LRC is an alternative to the original BFP algorithm in that it processes utterances incrementally. It works by first searching for an antecedent in the current sentence; if none can be found, it continues the search on the Cf-list of the previous and the other preceding utterances in a left-to-right fashion. In her squib, Byron maintains that additional kinds of information should be included in an evaluation in order to make the performance of algorithms on pronoun resolution more transparent. In particular, she suggests that the pronoun coverage be explicitly reported and proposes that the evaluation details be presented in a concise and compact tabular format called standard disclosure.

Background

acl_arc_intent_classification:train:438

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: None Context before the citation: Lapalme and Kosseim (2003) investigated three approaches to the automatic generation of response e-mails: text classification, case-based reasoning, and question answering. In addition, rather than including actual response sentences in a reply, their system matches response sentences to pre-existing templates and returns the templates. This part of their approach resembles our Doc-Ret method, but instead of retrieving entire response documents, they retrieve individual sentences. Citation Sentence: Lapalme and Kosseim ( 2003 ) investigated three approaches to the automatic generation of response e-mails : text classification , case-based reasoning , and question answering . Context after the citation: Text classification was used to group request e-mails into broad categories, some of which, such as requests for financial reports, can be automatically addressed. The question-answering approach and the retrieval component of the case-based reasoning approach were data driven, using word-level matches. However, the personalization component of the case-based reasoning approach was rule-based (e.g., rules were applied to substitute names of individuals and companies in texts). With respect to these systems, the contribution of our work lies in the consideration of different kinds of corpus-based approaches (namely, retrieval and prediction) applied at different levels of granularity (namely, document and sentence).

CompareOrContrast

acl_arc_intent_classification:train:439

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: method Context before the citation: We can define PCAT using a probabilistic grammar (Garrette et al., 2014). To formalize the notion of what it means for a category to be more “plausible”, we extend the category generator of our previous work, which we will call PCAT. For the root, binary, and unary parameters, we want to choose prior means that encode our bias toward cross-linguistically-plausible categories. Citation Sentence: We can define PCAT using a probabilistic grammar ( Garrette et al. , 2014 ) . Context after the citation: The grammar may first generate a start or end category ((S),(E)) with probability pse or a special tokendeletion category ((D); explained in §5) with probability pdel, or a standard CCG category C: For each sentence s, there will be one (S) and one (E), so we set pse = 1/(25 + 2), since the average sentence length in the corpora is roughly 25. To discourage the model from deleting tokens (only applies during testing), we set pdel = 10−100. For PC, the distribution over standard categories, we use a recursive definition based on the structure of a CCG category.

Background

acl_arc_intent_classification:train:44

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: method Context before the citation: This contrasts with one of the traditional approaches (e.g., Dorr 1994; Watanabe 1995) to posing the translation problem, i.e., the approach in which translation problems are seen in terms of bridging the gap between the most natural monolingual representations underlying the sentences of each language. For example, headwords in both languages are chosen to force a synchronized alignment (for better or worse) in order to simplify cases involving so-called head-switching. Instead, the aim is to produce bilingual (i.e., synchronized, see below) dependency representations that are appropriate to performing the translation task for a specific language pair or specific bilingual corpus. Citation Sentence: This contrasts with one of the traditional approaches ( e.g. , Dorr 1994 ; Watanabe 1995 ) to posing the translation problem , i.e. , the approach in which translation problems are seen in terms of bridging the gap between the most natural monolingual representations underlying the sentences of each language . Context after the citation: The training method has four stages: (i) Compute co-occurrence statistics from the training data. (ii) Search for an optimal synchronized hierarchical alignment for each bitext. (iii) Construct a set of head transducers that can generate these alignments with transition weights derived from maximum likelihood estimation.

CompareOrContrast

acl_arc_intent_classification:train:440

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: introduction Context before the citation: In practical context, German, English, and Japanese HPSG-based grammars are developed and used in the Verbmobil project (Kay et al., 1994). Stanford University is developing the English Resource Grammar, an HPSG grammar for English, as a part of the Linguistic Grammars Online (LinGO) project (Flickinger, 2000). There are a variety of works on efficient parsing with HPSG, which allow the use of HPSGbased processing in practical application contexts (Flickinger et al., 2000). Citation Sentence: In practical context , German , English , and Japanese HPSG-based grammars are developed and used in the Verbmobil project ( Kay et al. , 1994 ) . Context after the citation: Our group has developed a wide-coverage HPSG grammar for Japanese (Mitsuishi et al., 1998), which is used in a high-accuracy Japanese dependency analyzer (Kanayama et al., 2000).

Background

acl_arc_intent_classification:train:441

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: introduction Context before the citation: Thus, over the past few years, along with advances in the use of learning and statistical methods for acquisition of full parsers (Collins, 1997; Charniak, 1997a; Charniak, 1997b; Ratnaparkhi, 1997), significant progress has been made on the use of statistical learning methods to recognize shallow parsing patterns syntactic phrases or words that participate in a syntactic relationship (Church, 1988; Ramshaw and Marcus, 1995; Argamon et al., 1998; Cardie and Pierce, 1998; Munoz et al., 1999; Punyakanok and Roth, 2001; Buchholz et al., 1999; Tjong Kim Sang and Buchholz, 2000). While earlier work in this direction concentrated on manual construction of rules, most of the recent work has been motivated by the observation that shallow syntactic information can be extracted using local information by examining the pattern itself, its nearby context and the local part-of-speech information. to ] [NP only $ 1.8 billion ] [PP in ] [NP September] . Citation Sentence: Thus , over the past few years , along with advances in the use of learning and statistical methods for acquisition of full parsers ( Collins , 1997 ; Charniak , 1997a ; Charniak , 1997b ; Ratnaparkhi , 1997 ) , significant progress has been made on the use of statistical learning methods to recognize shallow parsing patterns syntactic phrases or words that participate in a syntactic relationship ( Church , 1988 ; Ramshaw and Marcus , 1995 ; Argamon et al. , 1998 ; Cardie and Pierce , 1998 ; Munoz et al. , 1999 ; Punyakanok and Roth , 2001 ; Buchholz et al. , 1999 ; Tjong Kim Sang and Buchholz , 2000 ) . Context after the citation: Research on shallow parsing was inspired by psycholinguistics arguments (Gee and Grosjean, 1983) that suggest that in many scenarios (e.g., conversational) full parsing is not a realistic strategy for sentence processing and analysis, and was further motivated by several arguments from a natural language engineering viewpoint. First, it has been noted that in many natural language applications it is sufficient to use shallow parsing information; information such as noun phrases (NPs) and other syntactic sequences have been found useful in many large-scale language processing applications including information extraction and text summarization (Grishman, 1995; Appelt et al., 1993). Second, while training a full parser requires a collection of fully parsed sentences as training corpus, it is possible to train a shallow parser incrementally. If all that is available is a collection of sentences annotated for NPs, it can be used to produce this level of analysis.

Background

acl_arc_intent_classification:train:442

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: None Context before the citation: For example, such schema can serve as a mean to represent translation examples, or find structural correspondences for the purpose of transfer grammar learning (Menezes & Richardson, 2001), (Aramaki et al., 2001), (Watanabe et al., 2000), (Meyers et al., 2000), (Matsumoto et al., 1993), (kaji et al., 1992), and example-base machine translation EBMT3 (Sato & Nagao, 1990), (Sato, 1991), (Richardson et al., 2001), (Al-Adhaileh & Tang, 1999). Due to these limitations, instead of investigating into the synchronization of two grammars, we propose a flexible annotation schema (i.e. Synchronous Structured String-Tree Correspondence (S-SSTC)) to realize additional power and flexibility in expressing structural correspondences at the level of language sentence pairs. Similar limitations also appear in synchronous CFGs (Harbusch & Poller,1994). Citation Sentence: For example , such schema can serve as a mean to represent translation examples , or find structural correspondences for the purpose of transfer grammar learning ( Menezes & Richardson , 2001 ) , ( Aramaki et al. , 2001 ) , ( Watanabe et al. , 2000 ) , ( Meyers et al. , 2000 ) , ( Matsumoto et al. , 1993 ) , ( kaji et al. , 1992 ) , and example-base machine translation EBMT3 ( Sato & Nagao , 1990 ) , ( Sato , 1991 ) , ( Richardson et al. , 2001 ) , ( Al-Adhaileh & Tang , 1999 ) . Context after the citation:

Background

acl_arc_intent_classification:train:443

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: experiments Context before the citation: While IA is generally thought to be consistent with findings on human language production (Hermann and Deutsch 1976; Levelt 1989; Pechmann 1989; Sonnenschein 1982), the hypothesis that incrementality is a good model of human GRE seems unfalsifiable until a preference order is specified for the properties on which it operates. Citation Sentence: While IA is generally thought to be consistent with findings on human language production ( Hermann and Deutsch 1976 ; Levelt 1989 ; Pechmann 1989 ; Sonnenschein 1982 ) , the hypothesis that incrementality is a good model of human GRE seems unfalsifiable until a preference order is specified for the properties on which it operates . Context after the citation: (Wildly redundant descriptions can result if the ‘wrong’ preference order are chosen.) We shall see that vague descriptions pose particular challenges to incrementality. One question emerges when the IA is combined with findings on word order and incremental interpretation. If human speakers and/or writers perform CD incrementally, then why are properties not expressed in the same order in which they were selected?

Background

acl_arc_intent_classification:train:444

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: related work Context before the citation: It helps them build complex knowledge bases by combining components: events, entities and modifiers (Clark and Porter, 1997). In the Rapid Knowledge Formation Project (RKF) a support system was developed for domain experts. Lists of semantic relations are designed to capture salient domain information. Citation Sentence: It helps them build complex knowledge bases by combining components : events , entities and modifiers ( Clark and Porter , 1997 ) . Context after the citation: The system’s interface facilitates the expert’s task of creating and manipulating structures which represent domain concepts, and assigning them relations from a relation dictionary. In current work on semantic relation analysis, the focus is on semantic roles – relations between verbs and their arguments. Most approaches rely on VerbNet (Kipper et al., 2000) and FrameNet (Baker et al., 1998) to provide associations between verbs and semantic roles, that are then mapped onto the current instance, as shown by the systems competing in semantic role labelling competitions (Carreras and Marquez, 2004; Carreras and Marquez, 2005) and also (Gildea and Jurafsky, 2002; Pradhan et al., 2005; Shi and Mihalcea, 2005). These systems share two ideas which make them different from the approach presented here: they all analyse verb-argument relations, and they all use machine learning or probabilistic approaches (Pradhan et al., 2005) to assign a label to a new instance.

Background

acl_arc_intent_classification:train:445

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: introduction Context before the citation: Our group has developed a wide-coverage HPSG grammar for Japanese (Mitsuishi et al., 1998), which is used in a high-accuracy Japanese dependency analyzer (Kanayama et al., 2000). In practical context, German, English, and Japanese HPSG-based grammars are developed and used in the Verbmobil project (Kay et al., 1994). Stanford University is developing the English Resource Grammar, an HPSG grammar for English, as a part of the Linguistic Grammars Online (LinGO) project (Flickinger, 2000). Citation Sentence: Our group has developed a wide-coverage HPSG grammar for Japanese ( Mitsuishi et al. , 1998 ) , which is used in a high-accuracy Japanese dependency analyzer ( Kanayama et al. , 2000 ) . Context after the citation:

Background

acl_arc_intent_classification:train:446

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: related work Context before the citation: Word frequency counts in internet search engines are inconsistent and unreliable (Veronis, 2005). A key concern in corpus linguistics and related disciplines is verifiability and replicability of the results of studies. Prototypes of Internet search engines for linguists, corpus linguists and lexicographers have been proposed: WebCorp (Kehoe and Renouf, 2002), KWiCFinder (Fletcher, 2004a) and the Linguist’s Search Engine (Kilgarriff, 2003; Resnik and Elkiss, 2003). Citation Sentence: Word frequency counts in internet search engines are inconsistent and unreliable ( Veronis , 2005 ) . Context after the citation: Tools based on static corpora do not suffer from this problem, e.g. BNCweb7, developed at the University of Zurich, and View 8 (Variation in English Words and Phrases, developed at Brigham Young University) 4 http://www.comp.lancs.ac.uk/ucrel/claws/trial.html 5 http://www.comp.leeds.ac.uk/amalgam/amalgam/ amalghome.htm 6 http://www.connexor.com 7 http://homepage.mac.com/bncweb/home.html 8 http://view.byu.edu/ are both based on the British National Corpus. Both BNCweb and View enable access to annotated corpora and facilitate searching on part-ofspeech tags.

Background

acl_arc_intent_classification:train:447

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: None Context before the citation: Other milestones of recent research include the deployment of probabilistic and machine learning techniques (Aone and Bennett 1995; Kehler 1997; Ge, Hale, and Charniak 1998; Cardie and Wagstaff 1999; the continuing interest in centering, used either in original or in revised form (Abracos and Lopes 1994; Strube and Hahn 1996; Hahn and Strube 1997; Tetreault 1999); and proposals related to the evaluation methodology in anaphora resolution (Mitkov 1998a, 2001b). Against the background of a growing interest in multilingual NLP, multilingual anaphora /coreference resolution has gained considerable momentum in recent years (Aone and McKee 1993; Azzam, Humphreys, and Gaizauskas 1998; Harabagiu and Maiorano 2000; Mitkov and Barbu 2000; Mitkov 1999; Mitkov and Stys 1997; Mitkov, Belguith, and Stys 1998). The last decade of the 20th century saw a number of anaphora resolution projects for languages other than English such as French, German, Japanese, Spanish, Portuguese, and Turkish. Citation Sentence: Other milestones of recent research include the deployment of probabilistic and machine learning techniques ( Aone and Bennett 1995 ; Kehler 1997 ; Ge , Hale , and Charniak 1998 ; Cardie and Wagstaff 1999 ; the continuing interest in centering , used either in original or in revised form ( Abracos and Lopes 1994 ; Strube and Hahn 1996 ; Hahn and Strube 1997 ; Tetreault 1999 ) ; and proposals related to the evaluation methodology in anaphora resolution ( Mitkov 1998a , 2001b ) . Context after the citation: For a more detailed survey of the state of the art in anaphora resolution, see Mitkov (forthcoming). The papers published in this issue reflect the major trends in anaphora resolution in recent years. Some of them describe approaches that do not exploit full syntactic knowledge (as in the case of Palomar et al.'s and Stuckardt's work) or that employ machine learning techniques (Soon, Ng, and Lim); others present centering-based pronoun resolution (Tetreault) or discuss theoretical centering issues (Kibble). Almost all of the papers feature extensive evaluation (including comparative evaluation as in the case of Tetreault's and Palomar et al.'s work) or discuss general evaluation issues (Byron as well as Stuckardt).

Background

acl_arc_intent_classification:train:448

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: related work Context before the citation: It is only recently that the web name ambiguity has been approached as a separate problem and defined as an NLP task Web People Search on its own (Artiles et al., 2005; Artiles et al., 2007). Most of early research work on person name ambiguity focuses on the CDC problem or uses methods found in the WSD literature. The disambiguation of person names in Web results is usually compared to two other Natural Language Processing tasks: Word Sense Disambiguation (WSD) (Agirre and Edmonds, 2006) and Cross-document Coreference (CDC) (Bagga and Baldwin, 1998). Citation Sentence: It is only recently that the web name ambiguity has been approached as a separate problem and defined as an NLP task Web People Search on its own ( Artiles et al. , 2005 ; Artiles et al. , 2007 ) . Context after the citation: Therefore, it is useful to point out some crucial differences between WSD, CRC and WePS: • WSD typically concentrates in the disambiguation of common words (nouns, verbs, adjectives) for which a relatively small number of senses exist, compared to the hundreds or thousands of people that can share the same name. • WSD can rely on dictionaries to define the number of possible senses for a word. In the case of name ambiguity no such dictionary is available, even though in theory there is an exact number of people that can be accounted as sharing the same name.

Background

acl_arc_intent_classification:train:449

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: introduction Context before the citation: It is these orthographic variations and complex morphological structure that make Arabic language processing challenging (Xu et al., 2001; Xu et al., 2002). derivational and inflectional process, most prepositions, conjunctions, pronouns, and possessive forms are attached to the Arabic surface word. In addition to the different forms of the Arabic word that result from the Citation Sentence: It is these orthographic variations and complex morphological structure that make Arabic language processing challenging ( Xu et al. , 2001 ; Xu et al. , 2002 ) . Context after the citation: Both tasks are performed with a statistical framework: the mention detection system is similar to the one presented in (Florian et al., 2004) and the coreference resolution system is similar to the one described in (Luo et al., 2004). Both systems are built around from the maximum-entropy technique (Berger et al., 1996). We formulate the mention detection task as a sequence classification problem. While this approach is language independent, it must be modified to accomodate the particulars of the Arabic language.

Background

acl_arc_intent_classification:train:45

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: experiments Context before the citation: Actually, if we use LSH technique (Andoni and Indyk, 2008) in retrieval process, the local method can be easily scaled to a larger training data. Further, compared to the retrieval, the local training is not the bottleneck. This shows that the local method is efficient. Citation Sentence: Actually , if we use LSH technique ( Andoni and Indyk , 2008 ) in retrieval process , the local method can be easily scaled to a larger training data . Context after the citation:

FutureWork

acl_arc_intent_classification:train:450

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: method Context before the citation: Many lexicons, both automatically acquired and manually created, are more fine grained in their approaches to subcategorized clausal arguments, differentiating, for example, between a that-clause and a to + infinitive clause (Ushioda et al. 1993). However, as it stands, neither of these functions betrays anything about the syntactic nature of the constructs in question. The syntactic functions COMP and XCOMP refer to clausal complements with different predicate control patterns as described in Section 2. Citation Sentence: Many lexicons , both automatically acquired and manually created , are more fine grained in their approaches to subcategorized clausal arguments , differentiating , for example , between a that-clause and a to + infinitive clause ( Ushioda et al. 1993 ) . Context after the citation: With only a slight modification, our system, along with the details provided by the automatically generated f-structures, allows us to extract frames with an equivalent level of detail. For example, to identify a that-clause, we use Figure 5 Automatically generated f-structure for the Penn-II Treebank string wsj 0003 23. By 1997, almost all remaining uses of cancer-causing asbestos will be outlawed. the feature-value pair that:+ at f-structure level to read off the following subcategorization frame for the verb add: add([subj,comp(that)]).

Background

acl_arc_intent_classification:train:451

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: introduction Context before the citation: Others provide automatic mappings of natural language instructions to executable actions, such as interpreting navigation directions (Chen and Mooney, 2011) or robot commands (Tellex et al., 2011; Matuszek et al., 2012). Some approaches apply semantic parsing, where words and sentences are mapped to logical structure meaning (Kate and Mooney, 2007). The language grounding problem has come in many different flavors with just as many different approaches. Citation Sentence: Others provide automatic mappings of natural language instructions to executable actions , such as interpreting navigation directions ( Chen and Mooney , 2011 ) or robot commands ( Tellex et al. , 2011 ; Matuszek et al. , 2012 ) . Context after the citation: Some efforts have tackled tasks such as automatic image caption generation (Feng and Lapata, 2010a; Ordonez et al., 2011), text illustration (Joshi et al., 2006), or automatic location identification of Twitter users (Eisenstein et al., 2010; Wing and Baldridge, 2011; Roller et al., 2012). Another line of research approaches grounded language knowledge by augmenting distributional approaches of word meaning with perceptual information (Andrews et al., 2009; Steyvers, 2010; Feng and Lapata, 2010b; Bruni et al., 2011; Silberer and Lapata, 2012; Johns and Jones, 2012; Bruni et al., 2012a; Bruni et al., 2012b; Silberer et al., 2013). Although these approaches have differed in model definition, the general goal in this line of research has been to enhance word meaning with perceptual information in order to address one of the most common criticisms of distributional semantics: that the “meaning of words is entirely given by other words” (Bruni et al., 2012b). In this paper, we explore various ways to integrate new perceptual information through novel computational modeling of this grounded knowledge into a multimodal distributional model of word meaning.

Background

acl_arc_intent_classification:train:452

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: introduction Context before the citation: Agreement between two annotation sets is calculated here in terms of Cohen’s kappa (Cohen, 1960)1 and corrected kappa (Brennan and Prediger, 1981)2. A measure was derived for each annotated feature using the agreement analysis facility provided in ANVIL. However, one dialogue was coded independently and in parallel by two expert annotators to measure inter-coder agreement. Citation Sentence: Agreement between two annotation sets is calculated here in terms of Cohen 's kappa ( Cohen , 1960 ) 1 and corrected kappa ( Brennan and Prediger , 1981 ) 2 . Context after the citation: Anvil divides the annotations in slices and compares each slice. We used slices of 0.04 seconds. The inter-coder agreement figures obtained for the three types of annotation are given in Table 2. feature Cohen’s k corrected k agreement 73.59 98.74 dial act 84.53 98.87 turn 73.52 99.16 Table 2: Inter-coder agreement on feedback expression annotation Although researchers do not totally agree on how to measure agreement in various types of annotated data and on how to interpret the resulting figures, see Artstein and Poesio (2008), it is usually assumed that Cohen’s kappa figures over 60 are good while those over 75 are excellent (Fleiss, 1971).

Uses

acl_arc_intent_classification:train:453

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: introduction Context before the citation: Second, software for utilizing this ontology already exists: MetaMap (Aronson 2001) identifies concepts in free text, and SemRep (Rindflesch and Fiszman 2003) extracts relations between the concepts. First, substantial understanding of the domain has already been codified in the Unified Medical Language System (UMLS) (Lindberg, Humphreys, and McCray 1993). This domain is well-suited for exploring the posed research questions for several reasons. Citation Sentence: Second , software for utilizing this ontology already exists : MetaMap ( Aronson 2001 ) identifies concepts in free text , and SemRep ( Rindflesch and Fiszman 2003 ) extracts relations between the concepts . Context after the citation: Both systems utilize and propagate semantic information from UMLS knowledge sources: the Metathesaurus, the Semantic Network, and the SPECIALIST lexicon. The 2004 version of the UMLS Metathesaurus (used in this work) contains information about over 1 million biomedical concepts and 5 million concept names from more than 100 controlled vocabularies. The Semantic Network provides a consistent categorization of all concepts represented in the UMLS Metathesaurus. Third, the paradigm of evidence-based medicine (Sackett et al. 2000) provides a task-based model of the clinical information-seeking process.

Background

acl_arc_intent_classification:train:454

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: experiments Context before the citation: The implementation has been inspired by experience in extracting information from very large corpora (Curran and Moens, 2002) and performing experiments on maximum entropy sequence tagging (Curran and Clark, 2003; Clark et al., 2003). We can also load a lexicon into memory that is shared between all of the components, reducing the memory use. Further, we can use techniques for making string matching and other text processing very fast such as making only one copy of each lexical item or annotation in memory. Citation Sentence: The implementation has been inspired by experience in extracting information from very large corpora ( Curran and Moens , 2002 ) and performing experiments on maximum entropy sequence tagging ( Curran and Clark , 2003 ; Clark et al. , 2003 ) . Context after the citation: We have already implemented a POS tagger, chunker, CCG supertagger and named entity recogniser using the infrastructure. These tools currently train in less than 10 minutes on the standard training materials and tag faster than TNT, the fastest existing POS tagger. These tools use a highly optimised GIS implementation and provide sophisticated Gaussian smoothing (Chen and Rosenfeld, 1999). We expect even faster training times when we move to conjugate gradient methods.

Motivation

acl_arc_intent_classification:train:455

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: introduction Context before the citation: Some efforts have tackled tasks such as automatic image caption generation (Feng and Lapata, 2010a; Ordonez et al., 2011), text illustration (Joshi et al., 2006), or automatic location identification of Twitter users (Eisenstein et al., 2010; Wing and Baldridge, 2011; Roller et al., 2012). Others provide automatic mappings of natural language instructions to executable actions, such as interpreting navigation directions (Chen and Mooney, 2011) or robot commands (Tellex et al., 2011; Matuszek et al., 2012). Some approaches apply semantic parsing, where words and sentences are mapped to logical structure meaning (Kate and Mooney, 2007). Citation Sentence: Some efforts have tackled tasks such as automatic image caption generation ( Feng and Lapata , 2010a ; Ordonez et al. , 2011 ) , text illustration ( Joshi et al. , 2006 ) , or automatic location identification of Twitter users ( Eisenstein et al. , 2010 ; Wing and Baldridge , 2011 ; Roller et al. , 2012 ) . Context after the citation: Another line of research approaches grounded language knowledge by augmenting distributional approaches of word meaning with perceptual information (Andrews et al., 2009; Steyvers, 2010; Feng and Lapata, 2010b; Bruni et al., 2011; Silberer and Lapata, 2012; Johns and Jones, 2012; Bruni et al., 2012a; Bruni et al., 2012b; Silberer et al., 2013). Although these approaches have differed in model definition, the general goal in this line of research has been to enhance word meaning with perceptual information in order to address one of the most common criticisms of distributional semantics: that the “meaning of words is entirely given by other words” (Bruni et al., 2012b). In this paper, we explore various ways to integrate new perceptual information through novel computational modeling of this grounded knowledge into a multimodal distributional model of word meaning. The model we rely on was originally developed by

Background

acl_arc_intent_classification:train:456

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: conclusion Context before the citation: These types of features result in an improvement in both the mention detection and coreference resolution performance, as shown through experiments on the ACE 2004 Arabic data. Numbers under “ECMF&quot; are Entity-Constrained-Mention F-measure and numbers under “ACE-Val” are ACE-values. The row marked with “Truth” represents the results with “true” mentions while the row marked with “System” represents that mentions are detected by the system. Citation Sentence: These types of features result in an improvement in both the mention detection and coreference resolution performance , as shown through experiments on the ACE 2004 Arabic data . Context after the citation: The experiments are performed on a clearly specified partition of the data, so comparisons against the presented work can be correctly and accurately made in the future. In addition, we also report results on the official test data. The presented system has obtained competitive results in the ACE 2004 evaluation, being ranked amongst the top competitors.

Uses

acl_arc_intent_classification:train:457

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: related work Context before the citation: The use of the web as a corpus for teaching and research on language has been proposed a number of times (Kilgarriff, 2001; Robb, 2003; Rundell, 2000; Fletcher, 2001, 2004b) and received a special issue of the journal Computational Linguistics (Kilgarriff and Grefenstette, 2003). This corpus annotation bottleneck becomes even more problematic for voluminous data sets drawn from the web. Larger systems to support multiple document tagging processes would require resources that cannot be realistically provided by existing single-server systems. Citation Sentence: The use of the web as a corpus for teaching and research on language has been proposed a number of times ( Kilgarriff , 2001 ; Robb , 2003 ; Rundell , 2000 ; Fletcher , 2001 , 2004b ) and received a special issue of the journal Computational Linguistics ( Kilgarriff and Grefenstette , 2003 ) . Context after the citation: Studies have used several different methods to mine web data. Turney (2001) extracts word co-occurrence probabilities from unlabelled text collected from a web crawler. Baroni and Bernardini (2004) built a corpus by iteratively searching Google for a small set of seed terms. Prototypes of Internet search engines for linguists, corpus linguists and lexicographers have been proposed: WebCorp (Kehoe and Renouf, 2002), KWiCFinder (Fletcher, 2004a) and the Linguist’s Search Engine (Kilgarriff, 2003; Resnik and Elkiss, 2003).

Background

acl_arc_intent_classification:train:458

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: introduction Context before the citation: But while Bod's estimator obtains state-of-the-art results on the WSJ, comparable to Charniak (2000) and Collins (2000), Bonnema et al.'s estimator performs worse and is comparable to Collins (1996). We show that these PCFG-reductions result in a 60 times speedup in processing time w.r.t. Bod (2001, 2003). This paper presents the first published results with Goodman's PCFG-reductions of both Bonnema et al.'s (1999) and Bod's (2001) estimators on the WSJ. Citation Sentence: But while Bod 's estimator obtains state-of-the-art results on the WSJ , comparable to Charniak ( 2000 ) and Collins ( 2000 ) , Bonnema et al. 's estimator performs worse and is comparable to Collins ( 1996 ) . Context after the citation: In the second part of this paper, we extend our experiments with a new notion of the best parse tree. Most previous notions of best parse tree in DOP1 were based on a probabilistic metric, with Bod (2000b) as a notable exception, who used a simplicity metric based on the shortest derivation. We show that a combination of a probabilistic and a simplicity metric, which chooses the simplest parse from the n likeliest parses, outperforms the use of these metrics alone.

Background

acl_arc_intent_classification:train:459

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: experiments Context before the citation: The first is the one used in the chunking competition in CoNLL-2000 (Tjong Kim Sang and Buchholz, 2000). Both can be formally defined and they reflect different levels of shallow parsing patterns. For the purpose of this study, we chose to use two different definitions. Citation Sentence: The first is the one used in the chunking competition in CoNLL-2000 ( Tjong Kim Sang and Buchholz , 2000 ) . Context after the citation: In this case, a full parse tree is represented in a flat form, producing a representation as in the example above. The goal in this case is therefore to accurately predict a collection of different types of phrases. The chunk types are based on the syntactic category part of the bracket label in the Treebank. Roughly, a chunk contains everything to the left of and including the syntactic head of the constituent of the same name.

Uses

acl_arc_intent_classification:train:46

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: experiments Context before the citation: The implementation has been inspired by experience in extracting information from very large corpora (Curran and Moens, 2002) and performing experiments on maximum entropy sequence tagging (Curran and Clark, 2003; Clark et al., 2003). We can also load a lexicon into memory that is shared between all of the components, reducing the memory use. Further, we can use techniques for making string matching and other text processing very fast such as making only one copy of each lexical item or annotation in memory. Citation Sentence: The implementation has been inspired by experience in extracting information from very large corpora ( Curran and Moens , 2002 ) and performing experiments on maximum entropy sequence tagging ( Curran and Clark , 2003 ; Clark et al. , 2003 ) . Context after the citation: We have already implemented a POS tagger, chunker, CCG supertagger and named entity recogniser using the infrastructure. These tools currently train in less than 10 minutes on the standard training materials and tag faster than TNT, the fastest existing POS tagger. These tools use a highly optimised GIS implementation and provide sophisticated Gaussian smoothing (Chen and Rosenfeld, 1999). We expect even faster training times when we move to conjugate gradient methods.

Motivation

acl_arc_intent_classification:train:460

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: introduction Context before the citation: Another line of research approaches grounded language knowledge by augmenting distributional approaches of word meaning with perceptual information (Andrews et al., 2009; Steyvers, 2010; Feng and Lapata, 2010b; Bruni et al., 2011; Silberer and Lapata, 2012; Johns and Jones, 2012; Bruni et al., 2012a; Bruni et al., 2012b; Silberer et al., 2013). Some efforts have tackled tasks such as automatic image caption generation (Feng and Lapata, 2010a; Ordonez et al., 2011), text illustration (Joshi et al., 2006), or automatic location identification of Twitter users (Eisenstein et al., 2010; Wing and Baldridge, 2011; Roller et al., 2012). Others provide automatic mappings of natural language instructions to executable actions, such as interpreting navigation directions (Chen and Mooney, 2011) or robot commands (Tellex et al., 2011; Matuszek et al., 2012). Citation Sentence: Another line of research approaches grounded language knowledge by augmenting distributional approaches of word meaning with perceptual information ( Andrews et al. , 2009 ; Steyvers , 2010 ; Feng and Lapata , 2010b ; Bruni et al. , 2011 ; Silberer and Lapata , 2012 ; Johns and Jones , 2012 ; Bruni et al. , 2012a ; Bruni et al. , 2012b ; Silberer et al. , 2013 ) . Context after the citation: Although these approaches have differed in model definition, the general goal in this line of research has been to enhance word meaning with perceptual information in order to address one of the most common criticisms of distributional semantics: that the “meaning of words is entirely given by other words” (Bruni et al., 2012b). In this paper, we explore various ways to integrate new perceptual information through novel computational modeling of this grounded knowledge into a multimodal distributional model of word meaning. The model we rely on was originally developed by Andrews et al. (2009) and is based on a generalization of Latent Dirichlet Allocation.

Background

acl_arc_intent_classification:train:461

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: None Context before the citation: 14We parse each sentence with the Collins parser (Collins, 1999). We do not use any other lexical 0-features that reference x, for fear that they would enable the learner to explain the rationales without changing 0 as desired (see the end of section 5.3). To train our model, we use L-BFGS to locally maximize the log of the objective function (1):15 13These are the function words with count > 40 in a random sample of 100 documents, and which were associated with the O-I tag transition at more than twice the average rate. Citation Sentence: 14We parse each sentence with the Collins parser ( Collins , 1999 ) . Context after the citation: Then the document has one big parse tree, whose root is DOC, with each sentence being a child of DOC. 15One might expect this function to be convex because pe and po are both log-linear models with no hidden variables. However, log po(ri |xi, yi, 0) is not necessarily convex in 0. This defines ppoor from (1) to be a standard diagonal Gaussian prior, with variances σ2θ and σ2φ for the two sets of parameters.

Uses

acl_arc_intent_classification:train:462

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: conclusion Context before the citation: Encouraged by the success of chunk-based verb reordering lattices on ArabicEnglish (Bisazza and Federico, 2010), we tried to adapt the same approach to the German-English language pair. Word reordering between German and English is a complex problem. It would be interesting to compare the relative performance of the two approaches systematically. Citation Sentence: Encouraged by the success of chunk-based verb reordering lattices on ArabicEnglish ( Bisazza and Federico , 2010 ) , we tried to adapt the same approach to the German-English language pair . Context after the citation: It turned out that there is a larger variety of long reordering patterns in this case. Nevertheless, some experiments performed after the official evaluation showed promising results. We plan to pursue this work in several directions: Defining a lattice weighting scheme that distinguishes between original word order and reordering paths could help the decoder select the more promising path through the lattice.

Motivation

acl_arc_intent_classification:train:463

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: method Context before the citation: We followed the same experimental procedure as discussed in (Taft, 2004) for English polymorphemic words. In order to validate such claim we perform a lexical decision experiment using 32 native Bangla speakers with 92 different verb sequences. This leads us to the possibility that compositional verb sequences requires individual verbs to be recognized separately and thus the time to recognize such expressions must be greater than the non-compositional verbs which maps to a single expression of meaning. Citation Sentence: We followed the same experimental procedure as discussed in ( Taft , 2004 ) for English polymorphemic words . Context after the citation: However, rather than derived words, the subjects were shown a verb sequence and asked whether they recognize them as a valid combination. The reaction time (RT) of each subject is recorded. Our preliminarily observation from the RT analysis shows that as per our claim, RT of verb sequences having high compositionality value is significantly higher than the RTs for low or noncompositional verbs. This proves our hypothesis that Bangla compound verbs that show less compositionality are stored as a hole in the mental lexicon and thus follows the full-listing model whereas compositional verb phrases are individually parsed.

Uses

acl_arc_intent_classification:train:464

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: method Context before the citation: In our experiments, we employed the well-known classifier SVM&quot;ght to obtain individual-document classification scores, treating Y as the positive class and using plain unigrams as features.5 Following standard practice in sentiment analysis (Pang et al., 2002), the input to SVM&quot;ght consisted of normalized presence-of-feature (rather than frequency-of-feature) vectors. Citation Sentence: In our experiments , we employed the well-known classifier SVM `` ght to obtain individual-document classification scores , treating Y as the positive class and using plain unigrams as features .5 Following standard practice in sentiment analysis ( Pang et al. , 2002 ) , the input to SVM `` ght consisted of normalized presence-of-feature ( rather than frequency-of-feature ) vectors . Context after the citation: The ind value 5SVMlight is available at svmlight.joachims.org. Default parameters were used, although experimentation with different parameter settings is an important direction for future work (Daelemans and Hoste, 2002; Munson et al., 2005). for each speech segment s was based on the signed distance d(s) from the vector representing s to the trained SVM decision plane: where σs is the standard deviation of d(s) over all speech segments s in the debate in question, and ind(s, N) def = 1 − ind(s, Y).

Uses

acl_arc_intent_classification:train:465

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: None Context before the citation: The problem of handling ill-formed input has been studied by Carbonell and Hayes (1983), Granger (1983), Jensen et al. (1983), Kwasny and Sondheimer (1981), Riesbeck and Schank (1976), Thompson (1980), Weischedel and Black (1980), and Weischedel and Sondheimer (1983). A detailed description of the kinds of expectation mechanisms appearing in these systems appears in Fink (1983). While some of these systems did exhibit expectation capabilities at the sentence level, none acquired dialogues of the kind described here for the sake of dialogue level expectation and error correction. Citation Sentence: The problem of handling ill-formed input has been studied by Carbonell and Hayes ( 1983 ) , Granger ( 1983 ) , Jensen et al. ( 1983 ) , Kwasny and Sondheimer ( 1981 ) , Riesbeck and Schank ( 1976 ) , Thompson ( 1980 ) , Weischedel and Black ( 1980 ) , and Weischedel and Sondheimer ( 1983 ) . Context after the citation: A wide variety of techniques have been developed for addressing problems at the word, phrase, sentence, and in some cases, dialogue level. However, these methodologies have not used historical information at the dialogue level as described here. In most cases, the goal of these systems is to characterize the ill-formed input into classes of errors and to correct on that basis. The work described here makes no attempt to classify the errors, but treats them as random events that occur at any point in a sentence.

CompareOrContrast

acl_arc_intent_classification:train:466

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: None Context before the citation: To address this problem, we are currently working on developing a metagrammar in the sense of (Candito, 1999). Generally, the problem is not so much to state the correspondances between synonymic but syntactically different constructs as to do this in a general way while not overgeneralising. For instance, as Figures 3, 4 and 5 show, the FTAG trees assigned on syntactic grounds by Anne Abeill´e FTAG to predicative nouns, support verb constructions and transitive verbs can be equiped with a flat semantics in such a way as to assign the three sentences in 1 a unique semantic representation namely the one given above. Citation Sentence: To address this problem , we are currently working on developing a metagrammar in the sense of ( Candito , 1999 ) . Context after the citation: This metagrammar allows us to factorise both syntactic and semantic information. Syntactic information is factorised in the usual way. For instance, there will be a class NOVN1 which groups together all the initial trees representing the possible syntactic configurations in which a transitive verb with two nominal arguments can occur.

FutureWork

acl_arc_intent_classification:train:467

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: introduction Context before the citation: Sentences like 12, from Chomsky (1965), are frequently cited. For example, in considering the connection between syntax and phrasing, the linguistic literature most often refers to examples of embedded sentences. However, this claim is controversial because of the misa:ignments that occur between the two levels of phrasing. Citation Sentence: Sentences like 12 , from Chomsky ( 1965 ) , are frequently cited . Context after the citation: (Square brackets mark off the NP constituents that contain embedded sentences.) 12. This is [Nip the cat that caught [NI, the rat that stole [NI, the cheese] ] ] In such cases, the syntactic constituency indicated by bracketing is not in alignment with the prosodic phrasing. Instead, 12 has the prosodic phrasing in 13a.

Background

acl_arc_intent_classification:train:468

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: introduction Context before the citation: After the PropBank (Xue and Palmer 2003) was built, Xue and Palmer (2005) and Xue (2008) have produced more complete and systematic research on Chinese SRL. This paper made the first attempt on Chinese SRL and produced promising results. They just labeled the predicate-argument structures of ten specified verbs to a small collection of Chinese sentences, and used Support Vector Machines to identify and classify the arguments. Citation Sentence: After the PropBank ( Xue and Palmer 2003 ) was built , Xue and Palmer ( 2005 ) and Xue ( 2008 ) have produced more complete and systematic research on Chinese SRL . Context after the citation: Moschitti et al. (2005) has made some preliminary attempt on the idea of hierarchical semantic role labeling. However, without considerations on how to utilize the characteristics of linguistically similar semantic roles, the purpose of the hierarchical system is to simplify the classification process to make it less time consuming. So the hierarchical system in their paper performs a little worse than the traditional SRL systems, although it is more efficient.

Background

acl_arc_intent_classification:train:469