Dataframe with extracted metadata (table below with details) and full text of the collection for analysis : **size 489M**
| **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` | - |

```python
>>> 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](https://creativecommons.org/licenses/by-nc/4.0/). By using this corpus, you are agreeing to its usage terms.