The dataset viewer is not available for this dataset.
Cannot get the config names for the dataset.
Error code:   ConfigNamesError
Exception:    ReadTimeout
Message:      (ReadTimeoutError("HTTPSConnectionPool(host='huggingface.co', port=443): Read timed out. (read timeout=10)"), '(Request ID: 4c2da59a-7852-4214-ad86-d8a84c4e8644)')
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/dataset/config_names.py", line 79, in compute_config_names_response
                  config_names = get_dataset_config_names(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 347, in get_dataset_config_names
                  dataset_module = dataset_module_factory(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1910, in dataset_module_factory
                  raise e1 from None
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1885, in dataset_module_factory
                  return HubDatasetModuleFactoryWithoutScript(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1263, in get_module
                  patterns = get_data_patterns(base_path, download_config=self.download_config)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/data_files.py", line 497, in get_data_patterns
                  return _get_data_files_patterns(resolver)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/data_files.py", line 272, in _get_data_files_patterns
                  data_files = pattern_resolver(pattern)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/data_files.py", line 384, in resolve_pattern
                  for filepath, info in fs.glob(pattern, detail=True, **glob_kwargs).items()
                File "/src/services/worker/.venv/lib/python3.9/site-packages/huggingface_hub/hf_file_system.py", line 416, in glob
                  path = self.resolve_path(path, revision=kwargs.get("revision")).unresolve()
                File "/src/services/worker/.venv/lib/python3.9/site-packages/huggingface_hub/hf_file_system.py", line 183, in resolve_path
                  repo_and_revision_exist, err = self._repo_and_revision_exist(repo_type, repo_id, revision)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/huggingface_hub/hf_file_system.py", line 131, in _repo_and_revision_exist
                  self._api.repo_info(repo_id, revision=revision, repo_type=repo_type, timeout=HF_HUB_ETAG_TIMEOUT)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/huggingface_hub/utils/_validators.py", line 114, in _inner_fn
                  return fn(*args, **kwargs)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/huggingface_hub/hf_api.py", line 2588, in repo_info
                  return method(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/huggingface_hub/utils/_validators.py", line 114, in _inner_fn
                  return fn(*args, **kwargs)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/huggingface_hub/hf_api.py", line 2445, in dataset_info
                  r = get_session().get(path, headers=headers, timeout=timeout, params=params)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/requests/sessions.py", line 602, in get
                  return self.request("GET", url, **kwargs)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/requests/sessions.py", line 589, in request
                  resp = self.send(prep, **send_kwargs)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/requests/sessions.py", line 703, in send
                  r = adapter.send(request, **kwargs)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/huggingface_hub/utils/_http.py", line 66, in send
                  return super().send(request, *args, **kwargs)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/requests/adapters.py", line 635, in send
                  raise ReadTimeout(e, request=request)
              requests.exceptions.ReadTimeout: (ReadTimeoutError("HTTPSConnectionPool(host='huggingface.co', port=443): Read timed out. (read timeout=10)"), '(Request ID: 4c2da59a-7852-4214-ad86-d8a84c4e8644)')

Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.

Dataset Card for ACL Anthology Corpus

License

This repository provides full-text and metadata to the ACL anthology collection (80k articles/posters as of September 2022) also including .pdf files and grobid extractions of the pdfs.

How is this different from what ACL anthology provides and what already exists?

  • We provide pdfs, full-text, references and other details extracted by grobid from the PDFs while ACL Anthology only provides abstracts.
  • There exists a similar corpus call ACL Anthology Network but is now showing its age with just 23k papers from Dec 2016.
>>> 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]

Dataset Summary

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

Languages

en, zh and others

Dataset Structure

Dataframe

Data Instances

Each row is a paper from ACL anthology

Data Fields

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 -

Dataset Creation

The corpus has all the papers in ACL anthology - as of September'22

Source Data

Additional Information

Licensing Information

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

Citation Information

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

@Misc{acl-ocl,
    author =       {Shaurya Rohatgi, Yanxia Qin, Benjamin Aw, Niranjana Unnithan, Min-Yen Kan},
    title =        {The ACL OCL Corpus: advancing Open science in Computational Linguistics},
    howpublished = {arXiv},
    year =         {2022},
    url =          {https://huggingface.co/datasets/ACL-OCL/ACL-OCL-Corpus}
}

Acknowledgements

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

Contributions

Thanks to @shauryr, Yanxia Qin and Benjamin Aw for adding this dataset.

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