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WINGNUS
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ACL-OCL

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	"title": "Universal Dependency Treebanks for Low-Resource Indian Languages: The Case of Bhojpuri",
	"authors": [
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	"first": "Atul",
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	"institution": "Charles University",
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	"first": "Daniel",
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	"last": "Zeman",
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	"institution": "Charles University",
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	"abstract": "This paper presents the first dependency treebank for Bhojpuri, a resource-poor language that belongs to the Indo-Aryan language family. The objective behind the Bhojpuri Treebank (BHTB) project is to create a substantial, syntactically annotated treebank which not only acts as a valuable resource in building language technological tools, also helps in cross-lingual learning and typological research. Currently, the treebank consists of 4,881 annotated tokens in accordance with the annotation scheme of Universal Dependencies (UD). A Bhojpuri tagger and parser were created using machine learning approach. The accuracy of the model is 57.49% UAS, 45.50% LAS, 79.69% UPOS accuracy and 77.64% XPOS accuracy. The paper describes the details of the project including a discussion on linguistic analysis and annotation process of the Bhojpuri UD treebank.",
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	"text": "This paper presents the first dependency treebank for Bhojpuri, a resource-poor language that belongs to the Indo-Aryan language family. The objective behind the Bhojpuri Treebank (BHTB) project is to create a substantial, syntactically annotated treebank which not only acts as a valuable resource in building language technological tools, also helps in cross-lingual learning and typological research. Currently, the treebank consists of 4,881 annotated tokens in accordance with the annotation scheme of Universal Dependencies (UD). A Bhojpuri tagger and parser were created using machine learning approach. The accuracy of the model is 57.49% UAS, 45.50% LAS, 79.69% UPOS accuracy and 77.64% XPOS accuracy. The paper describes the details of the project including a discussion on linguistic analysis and annotation process of the Bhojpuri UD treebank.",
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	"text": "Bhojpuri is an Indian language that belongs to the Indo-Aryan language group. It is spoken in the western part of Bihar, north-western part of Jharkhand, and the Purvanchal region of Uttar Pradesh. The number of speakers according to the present Census of India 1 is considerably large at 50,579,447. It should be noted that Bhojpuri is spoken not just in India but also in other countries such as Nepal, Trinidad, Mauritius, Guyana, Suriname, and Fiji (Verma, 2003; Ojha, 2019) . Since Bhojpuri was considered a dialect of Hindi for a long time, it did not attract much attention from linguists and hence remains among the many lesser known and less-resourced languages of India. With the rise in language technology for Indian languages, significant developments have been achieved in major Indian languages but contributions towards research in the lesser-known/low-resourced languages remain minimal. Most parsers and treebanks have been developed for the scheduled (official) languages; the non-scheduled and lesser known languages still have a long way to go. In its endevour to fill this gap, the present paper discusses the creation and development of Bhojpuri Universal Dependency (UD) treebank and parser. UD has been acknowledged as an emerging framework for cross-linguistically consistent grammatical annotation. There is an open community with over 300 contributors, who have produced 157 treebanks in 90 languages to date (as per the latest release of UD-v2.5 2 (Zeman et al., 2019) . The primary aim of this project is to facilitate multilingual parser development. The system will also take into account crosslingual learning and perform parsing research from the perspective of language typology. The syntactic part of the annotation scheme can be seen as an evolution of (universal) Stanford dependencies (De Marneffe et al., 2006; De Marneffe and Manning, 2008; De Marneffe et al., 2014) , while the lexical and morphological part builds on the Google universal part-of-speech tags (Petrov et al., 2012) , and the Interset Interlingua (Zeman, 2008) for morpho-syntactic tagsets. Section 2. discusses the language resources that have been created so far for the Bhojpuri language. While Bhojpuri has some considerable efforts in progress, it has no dependency treebank and parser. Section 3. discusses methodology to develop the Bhojpuri treebank. Section 4. presents a linguistic study and annotation of the Bhojpuri Dependency treebank while Sections 5. and 6. discuss the development of the Bhojpuri parser and evaluate its results. The final section ends with concluding remarks and future work.",
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	"section": "Introduction",
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	"text": "In 2013, a consortium was formed under the leadership of IIIT Hyderabad to start a project sponsored by TDIL, Government of India, and called The Development of Dependency Treebank for Indian Languages. 3 The fundamental objective of this project was to resurrect annotation work towards monolingual and parallel treebanks for languages such as Hindi, Marathi, Bengali, Kannada, and Malayalam. To accomplish this treebank model, the P\u0101\u1e47inian K\u0101raka Dependency annotation scheme was followed (Bharati et al., 2006) . The annotation scheme was previously also utilized to annotate data in Telugu, Urdu, and Kashmiri (Begum et al., 2008; Husain et al., 2010; Bhat, 2017) . Within the Universal Dependencies framework, as of UD release 2.5, treebanks and parsers are available for Sanskrit, Hindi, Urdu, Marathi, Tamil, and Telugu (Zeman et al., 2019; Ravishankar, 2017; Straka and Strakov\u00e1, 2019) . NLP research in Bhojpuri has led to the development of a statistical POS tagger (Ojha et al., 2015; Singh and Jha, 2015) , a machine-readable dictionary (Ojha, 2016) , a language identification tool (Kumar et al., 2018) , a Sanskrit-Bhojpuri machine translation system (Sinha and Jha, 2018) , and more recently an English-Bhojpuri machine translation system (Ojha, 2019) . Nevertheless, there is no prior work on Bhojpuri treebanking and parsing.",
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	"section": "Literature Review",
	"sec_num": "2."
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	"text": "The data for the treebank has been extracted from the Bhojpuri Language Technological Resources (BHLTR) project 4 (Ojha, 2019) . The data has been selected from the news and non-fiction domains. For this project, we use 5000 sentences (105,174 tokens) which were previously annotated with part-of-speech tags now used for language-specific tags representation in the XPOS. Out of 5000 sentences and 105,174 tokens, 254 sentences and 4881 tokens have been manually annotated at present, and released in UD 2.5. The Bhojpuri Treebank (BHTB) 5 follows the annotation guidelines of Universal Dependencies for part-ofspeech categories, morphological features, and dependency relations. Since Bhojpuri is closely related to Hindi and there is already a Hindi treebank in UD, we followed the Hindi tagset wherever possible. Besides, the universal part-of-speech tagset (UPOS), UD also permits a secondary tagset (XPOS), which is languagespecific and typically follows an established pre-UD practice. We use the Bureau of Indian Standards (BIS) POS tagset 6 here. This is a generic tagset for annotating Indian languages. The XPOS tags were already present in our input data and we obtained the UPOS tags through automatic conversion from XPOS. In addition to UPOS, we use 16 lexical and inflectional features defined in UD. The details of used morphological features, UPOS tags and UD relations and their statistics are demonstrated in Tables 1, 2 and 3.",
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	"section": "Data and Methodology",
	"sec_num": "3."
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	"text": "As discussed earlier, we followed UD v2 guidelines to annotate BHTB. We mention below some Bhojpuri constructions and their linguistics analysis under UD.",
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	"section": "Linguistic Analysis of Bhojpuri Dependency Treebank",
	"sec_num": "4."
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	"text": "\u2022 Nominal Predicate with Copula Figure 1 is an example of a nominal predicate with a copula. In the example, the copula \u0939\u093d (ha) is preceded by the nominal predicate \u0926\u0947 \u0936 (de\u015ba). In accordance with UD, the nominal \u0926\u0947 \u0936 is the root of the sentence and the verbal copula \u0939\u093d is attached to it via the relation cop, as shown in the figure. Figure 2 where a verb \u0917\u0907\u0932 (gaila) is combined with an auxiliary \u0930\u0939\u0928 (rahana). In UD, the verb is tagged as the root of the sentence and the auxiliary is related to it via the relation aux. In Figure 3 , the sentence has both a conjunct verb and a compound verb. The conjunct verb is formed by combining a noun \u0928\u091c\u0930 (najara) with the compound verb \u091a \u0932 \u0917\u0907\u0932 (cali gaila). Moreover, the compound verb is formed by combining the main verb \u091a \u0932 (cali) with the light verb \u0917\u0907\u0932 (gaila). In UD, the main verb \u091a \u0932 is marked as root and the noun \u0928\u091c\u0930 is related to it via the compound relation. The light verb \u0917\u0907\u0932, on the other hand, is related to the main verb via the relation aux.",
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	"start": 32,
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	"text": "Figure 1",
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	"text": "Figure 2",
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	"text": "Figure 3",
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	"section": "Linguistic Analysis of Bhojpuri Dependency Treebank",
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	"text": "\u2022 Coordination Figure 4 illustrates an example of a coordinate construction. The conjuncts \u0906\u0908\u0902 (\u0101\u012bm) and \u0938\u092a \u0930\u0935\u093e\u0930 \u0906\u0908\u0902 (sapariv\u0101ra \u0101\u012bm) are conjoined through the conjunction \u0906 (\u0101). In UD, the first conjunct serves as the technical head and the second conjunct is attached to it via the relation conj. The coordinating conjunction \u0906 is related to the following conjunct via the relation cc. \"He went to Japan.\" Figure 2 : A parallel sentence with simple verb construction in Bhojpuri (lines 2-3) and Hindi (lines 4-5)",
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	"section": "Linguistic Analysis of Bhojpuri Dependency Treebank",
	"sec_num": "4."
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	"text": "Initially, we conducted an experiment where the parser was trained on the Hindi UD treebank (HDTB) and applied to Bhojpuri. While the parsing quality suffers from the differences between the two languages, this is partially counterbalanced by the fact that the Hindi treebank is large: there are 16,647 training sentences (351,704 tokens). This experiment was evaluated on the first 50 manually annotated sentences (650 tokens) in Bhojpuri. We found that the Hindi parser gives only 56.77% UAS, 45.61% LAS, and 52.35% UPOS tagging accuracy, respectively (as shown in Table 4 ). Along with this, the tokenization accuracy of the Hindi model is only 89.15%. Since accuracy was very low, to improve it, we conducted three experiments solely based on Bhojpuri data to build a Bhojpuri parser. In all the three experiments, we used the UDPipe open source tool (Straka and Strakov\u00e1, 2017) . In all the cases, we used crossvalidation 90:10 average. We used UDPipe's default epoch size and learning rate, while the other hyperparameters were randomized. However, the three experiments differ in the data size: first experiment was conducted on 1000 tokens, the second experiment was conducted on 1500 tokens, and the third experiment was conducted on 4880 tokens. The results are discussed below in the evaluation section. ",
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	"text": "Table 4",
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	"section": "Development of a Bhojpuri Parser",
	"sec_num": "5."
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	"text": "The results of the three experiments with the Bhojpuri parser are shown in Table 5 and in Figure 6 . In terms of labeled attachment score, the results show that the third experiment, which was trained on 4880 tokens, produced slightly better result in comparison to the previous two experiments. The third experiment also performed better in comparison to the result of the Hindi parser that was used to tag the Bhojpuri data. This result is interesting. Even though Hindi is a closely related language and its parser is trained on a large amount of data (351,704 tokens), the Hindi parser couldn't perform any better on the Bhojpuri data. This shows that the same parser should not be used on two different languages even when they are closely related. We need to develop a separate and robust parser. ",
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	"start": 75,
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	"text": "Table 5",
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	"text": "Figure 6",
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	"section": "Evaluation",
	"sec_num": "6."
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	{
	"text": "This paper reports the development of the very first dependency treebank for Bhojpuri language using the annotation scheme of Universal Dependency (UD). The primary aim behind undertaking this project is to facilitate dependency treebank for Bhojpuri which is one of the low-resourced Indian languages. Currently, the Bhojpuri treebank consists of 4,881 tokens. This paper discussed the annotation guidelines used, the annotation process, and statistics of the used tags/UD relations. It also presented the linguistic analysis of the Bhojpuri treebank using examples from the language. Additionally, this paper presented a Bhojpuri parser which has been trained on UDPipe tool. The accuracy of the developed model is 57.49% UAS, 45.50% LAS, 79.69% UPOS and 77.64% XPOS. In the near future, we plan to extend BHTB up to 5,000 sentences and develop a parallel Bhojpuri-Hindi treebank. Along with this we will improve and develop a robust Bhojpuri parser using a neural model. \"Shailendra Mishra and Omprakash sang Bhojpuri songs in the program, which everyone enjoyed\" Figure 5 : A parallel sentence with clauses in Bhojpuri (lines 2-3) and Hindi (lines 4-5) Figure 6 : Learning curve of the Bhojpuri models.",
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	"text": "Figure 6",
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	"section": "Conclusion and Future Work",
	"sec_num": "7."
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	{
	"text": "http://www.censusindia.gov.in/2011Census/C-16_ 25062018_NEW.pdf 2 https://universaldependencies.org/",
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	{
	"text": "http://meity.gov.in/content/ language-computing-group-vi",
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	"back_matter": [
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	"text": "This work has been supported by LINDAT/CLA-RIAH-CZ and Khresmoi, the grants no. LM2018101 and 7E11042 of the Ministry of Education, Youth and Sports of the Czech Republic, and FP7-ICT-2010-6-257528 of the European Union.",
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	"section": "Acknowledgements",
	"sec_num": "8."
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	"FIGREF0": {
	"text": "and come with your family.\"Figure 4: A parallel sentence with coordination in Bhojpuri (lines 2-3) and Hindi (lines 4-5)",
	"type_str": "figure",
	"num": null,
	"uris": null
	},
	"TABREF1": {
	"num": null,
	"content": "<table><tr><td>UPOS Tags</td><td>Description</td><td>Count</td></tr><tr><td>ADJ</td><td>Adjective</td><td>183</td></tr><tr><td>ADP</td><td>Adposition</td><td>720</td></tr><tr><td>ADV</td><td>Adverb</td><td>18</td></tr><tr><td>AUX</td><td>Auxiliary</td><td>256</td></tr><tr><td>CCONJ</td><td>Coordinating conjunction</td><td>112</td></tr><tr><td>DET</td><td>Determiner</td><td>256</td></tr><tr><td>INTJ</td><td>Interjection</td><td>4</td></tr><tr><td>NOUN</td><td>Noun</td><td>1361</td></tr><tr><td>NUM</td><td>Numeral</td><td>110</td></tr><tr><td>PART</td><td>Particle</td><td>135</td></tr><tr><td>PRON</td><td>Pronoun</td><td>230</td></tr><tr><td>PROPN</td><td>Proper noun</td><td>352</td></tr><tr><td>PUNCT</td><td>Punctuation</td><td>504</td></tr><tr><td>SCONJ</td><td>Subordinating conjunction</td><td>86</td></tr><tr><td>VERB</td><td>Verb</td><td>553</td></tr><tr><td>X</td><td>Other</td><td>1</td></tr></table>",
	"html": null,
	"text": "Statistics of morphological features used in the BHTB",
	"type_str": "table"
	},
	"TABREF2": {
	"num": null,
	"content": "<table><tr><td>\u2022 Verbal Predicates</td></tr><tr><td>We discuss three types of verbal predicates in this</td></tr><tr><td>section: a simple verb construction, a conjunct</td></tr><tr><td>verb construction and a compound verb construc-</td></tr><tr><td>tion. A simple verb or a verb with auxiliary is</td></tr><tr><td>called simple verb construction. An example is</td></tr><tr><td>given in</td></tr></table>",
	"html": null,
	"text": "Statistics of UPOS tags used in the BHTB",
	"type_str": "table"
	},
	"TABREF4": {
	"num": null,
	"content": "<table/>",
	"html": null,
	"text": "",
	"type_str": "table"
	},
	"TABREF5": {
	"num": null,
	"content": "<table><tr><td colspan=\"5\">This is a common property of many Indo-Aryan</td></tr><tr><td colspan=\"2\">languages.</td><td/><td/></tr><tr><td/><td/><td>nsubj</td><td/><td>root</td></tr><tr><td/><td/><td/><td>obj</td></tr><tr><td>det</td><td/><td/><td colspan=\"2\">amod</td><td>cop</td></tr><tr><td colspan=\"3\">DET NOUN NOUN</td><td>ADJ</td><td>NOUN AUX</td></tr><tr><td>\u0908 \u012b</td><td>\u0926\u0947 \u0936 de\u015ba</td><td colspan=\"3\">\u093f\u092c\u0906\u0939 bi\u0101ha pradh\u0101na de\u015ba \u092a\u0930\u094d\u0927\u093e\u0928 \u0926\u0947 \u0936</td><td>\u0939\u093d ha</td></tr><tr><td colspan=\"5\">\u092f\u0939 yaha de\u015ba \u0926\u0947 \u0936 this country marriage oriented country is \u093f\u0935\u0935\u093e\u0939 \u092a\u0930\u094d\u0927\u093e\u0928 \u0926\u0947 \u0936 \u0939\u0948 viv\u0101ha pradh\u0101na de\u015ba hai</td></tr><tr><td colspan=\"5\">\"This country is a marriage-oriented country.\"</td></tr><tr><td colspan=\"5\">Figure 1: A parallel copular sentence in Bhojpuri (lines</td></tr><tr><td colspan=\"3\">2-3) and Hindi (lines 4-5).</td><td/></tr><tr><td/><td/><td>root</td><td/></tr><tr><td/><td/><td>nsubj</td><td>punct</td></tr><tr><td/><td/><td>obj</td><td>aux</td></tr><tr><td colspan=\"5\">PRON PROPN VERB AUX PUNCT</td></tr><tr><td colspan=\"2\">\u090a \u016b</td><td colspan=\"3\">\u091c\u093e\u092a\u093e\u0928 j\u0101p\u0101na gaila rahana \u0917\u0907\u0932 \u0930\u0939\u0928</td><td>\u0964 .</td></tr><tr><td colspan=\"3\">\u0935\u0939 vaha j\u0101p\u0101na gay\u0101 \u091c\u093e\u092a\u093e\u0928 \u0917\u092f\u093e</td><td>\u0925\u093e th\u0101</td><td>\u0964 .</td></tr><tr><td colspan=\"2\">he</td><td>Japan gone</td><td>was</td><td>.</td></tr></table>",
	"html": null,
	"text": "clausal complement(ccomp), open clausal complement (xcomp), adverbial clausal modifier (advcl), clausal modifier of noun (acl). We found all five types of clauses in Bhojpuri. We demonstrate here an example of a clausal modifier of noun. InFigure5, the clause \u091c\u0935\u0928\u093e \u0915\u0947 \u0938\u092d\u0947 \u0906\u0928\u0928\u094d\u0926 \u0932\u0939\u0932 (javan\u0101 ke sabhe \u0101nanda lihala) is a modifier of the noun \u0917\u0935\u0928\u0908 (gavana\u012b) which is shown by the tag acl. Interestingly, the clausal modifier is displaced from its base position and right adjoined to the verb.",
	"type_str": "table"
	},
	"TABREF8": {
	"num": null,
	"content": "<table><tr><td>: Accuracy of a UDPipe model trained on the</td></tr><tr><td>Hindi UD treebank (HDTB) and applied to the first</td></tr><tr><td>50 Bhojpuri sentences.</td></tr></table>",
	"html": null,
	"text": "",
	"type_str": "table"
	},
	"TABREF10": {
	"num": null,
	"content": "<table/>",
	"html": null,
	"text": "UDPipe accuracy of the conducted experiments",
	"type_str": "table"
	}
	}
	}
	}