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Dataset Card for "scicite"
Dataset Summary
This is a dataset for classifying citation intents in academic papers. The main citation intent label for each Json object is specified with the label key while the citation context is specified in with a context key. Example: { 'string': 'In chacma baboons, male-infant relationships can be linked to both formation of friendships and paternity success [30,31].' 'sectionName': 'Introduction', 'label': 'background', 'citingPaperId': '7a6b2d4b405439', 'citedPaperId': '9d1abadc55b5e0', ... } You may obtain the full information about the paper using the provided paper ids with the Semantic Scholar API (https://api.semanticscholar.org/). The labels are: Method, Background, Result
Supported Tasks and Leaderboards
Languages
Dataset Structure
Data Instances
default
- Size of downloaded dataset files: 23.19 MB
- Size of the generated dataset: 5.15 MB
- Total amount of disk used: 28.33 MB
An example of 'validation' looks as follows.
{
"citeEnd": 68,
"citeStart": 64,
"citedPaperId": "5e413c7872f5df231bf4a4f694504384560e98ca",
"citingPaperId": "8f1fbe460a901d994e9b81d69f77bfbe32719f4c",
"excerpt_index": 0,
"id": "8f1fbe460a901d994e9b81d69f77bfbe32719f4c>5e413c7872f5df231bf4a4f694504384560e98ca",
"isKeyCitation": false,
"label": 2,
"label2": 0,
"label2_confidence": 0.0,
"label_confidence": 0.0,
"sectionName": "Discussion",
"source": 4,
"string": "These results are in contrast with the findings of Santos et al.(16), who reported a significant association between low sedentary time and healthy CVF among Portuguese"
}
Data Fields
The data fields are the same among all splits.
default
string
: astring
feature.sectionName
: astring
feature.label
: a classification label, with possible values includingmethod
(0),background
(1),result
(2).citingPaperId
: astring
feature.citedPaperId
: astring
feature.excerpt_index
: aint32
feature.isKeyCitation
: abool
feature.label2
: a classification label, with possible values includingsupportive
(0),not_supportive
(1),cant_determine
(2),none
(3).citeEnd
: aint64
feature.citeStart
: aint64
feature.source
: a classification label, with possible values includingproperNoun
(0),andPhrase
(1),acronym
(2),etAlPhrase
(3),explicit
(4).label_confidence
: afloat32
feature.label2_confidence
: afloat32
feature.id
: astring
feature.
Data Splits
name | train | validation | test |
---|---|---|---|
default | 8194 | 916 | 1859 |
Dataset Creation
Curation Rationale
Source Data
Initial Data Collection and Normalization
Who are the source language producers?
Annotations
Annotation process
Who are the annotators?
Personal and Sensitive Information
Considerations for Using the Data
Social Impact of Dataset
Discussion of Biases
Other Known Limitations
Additional Information
Dataset Curators
Licensing Information
Citation Information
@inproceedings{cohan-etal-2019-structural,
title = "Structural Scaffolds for Citation Intent Classification in Scientific Publications",
author = "Cohan, Arman and
Ammar, Waleed and
van Zuylen, Madeleine and
Cady, Field",
booktitle = "Proceedings of the 2019 Conference of the North {A}merican Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers)",
month = jun,
year = "2019",
address = "Minneapolis, Minnesota",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/N19-1361",
doi = "10.18653/v1/N19-1361",
pages = "3586--3596",
}
Contributions
Thanks to @lewtun, @patrickvonplaten, @mariamabarham, @thomwolf for adding this dataset.
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Models trained or fine-tuned on allenai/scicite
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