Datasets:

WINGNUS
/

ACL-OCL

Column name	Description
`acl_id`	unique ACL id
`abstract`	abstract extracted by GROBID
`full_text`	full text extracted by GROBID
`corpus_paper_id`	Semantic Scholar ID
`pdf_hash`	sha1 hash of the pdf
`numcitedby`	number of citations from S2
`url`	link of publication
`publisher`	-
`address`	Address of conference
`year`	-
`month`	-
`booktitle`	-
`author`	list of authors
`title`	title of paper
`pages`	-
`doi`	-
`number`	-
`volume`	-
`journal`	-
`editor`	-
`isbn`	-

>>> import pandas as pd
>>> df = pd.read_parquet('acl-publication-info.74k.parquet')
>>> df
         acl_id                                           abstract                                          full_text  corpus_paper_id                                  pdf_hash  ...  number volume journal editor  isbn
0      O02-2002  There is a need to measure word similarity whe...  There is a need to measure word similarity whe...         18022704  0b09178ac8d17a92f16140365363d8df88c757d0  ...    None   None    None   None  None
1      L02-1310                                                                                                                8220988  8d5e31610bc82c2abc86bc20ceba684c97e66024  ...    None   None    None   None  None
2      R13-1042  Thread disentanglement is the task of separati...  Thread disentanglement is the task of separati...         16703040  3eb736b17a5acb583b9a9bd99837427753632cdb  ...    None   None    None   None  None
3      W05-0819  In this paper, we describe a word alignment al...  In this paper, we describe a word alignment al...          1215281  b20450f67116e59d1348fc472cfc09f96e348f55  ...    None   None    None   None  None
4      L02-1309                                                                                                               18078432  011e943b64a78dadc3440674419821ee080f0de3  ...    None   None    None   None  None
...         ...                                                ...                                                ...              ...                                       ...  ...     ...    ...     ...    ...   ...
73280  P99-1002  This paper describes recent progress and the a...  This paper describes recent progress and the a...           715160  ab17a01f142124744c6ae425f8a23011366ec3ee  ...    None   None    None   None  None
73281  P00-1009  We present an LFG-DOP parser which uses fragme...  We present an LFG-DOP parser which uses fragme...          1356246  ad005b3fd0c867667118482227e31d9378229751  ...    None   None    None   None  None
73282  P99-1056  The processes through which readers evoke ment...  The processes through which readers evoke ment...          7277828  924cf7a4836ebfc20ee094c30e61b949be049fb6  ...    None   None    None   None  None
73283  P99-1051  This paper examines the extent to which verb d...  This paper examines the extent to which verb d...          1829043  6b1f6f28ee36de69e8afac39461ee1158cd4d49a  ...    None   None    None   None  None
73284  P00-1013  Spoken dialogue managers have benefited from u...  Spoken dialogue managers have benefited from u...         10903652  483c818c09e39d9da47103fbf2da8aaa7acacf01  ...    None   None    None   None  None

[73285 rows x 21 columns]

We are hoping that this corpus can be helpful for analysis relevant to the ACL community.

Please cite/star 🌟 this page if you use this corpus

Citing the ACL Anthology Corpus

If you use this corpus in your research please use the following BibTeX entry:

@Misc{acl_anthology_corpus,
    author =       {Shaurya Rohatgi},
    title =        {ACL Anthology Corpus with Full Text},
    howpublished = {Github},
    year =         {2022},
    url =          {https://github.com/shauryr/ACL-anthology-corpus}
}

## Acknowledgements

We thank Semantic Scholar for providing access to the citation related data in this corpus.

License

ACL anthology corpus is released under the CC BY-NC 4.0. By using this corpus, you are agreeing to its usage terms.