google/tapas-base-finetuned-tabfact
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Updated
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Datasets:
Tasks:
Text Classification
Sub-tasks:
fact-checking
Languages:
English
Multilinguality:
monolingual
Size Categories:
100K<n<1M
Language Creators:
crowdsourced
Annotations Creators:
crowdsourced
Source Datasets:
original
ArXiv:
License:
cc-by-4.0
Dataset Preview
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Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code: StreamingRowsError
Exception: NonStreamableDatasetError
Message: Streaming is not possible for this dataset because data host server doesn't support HTTP range requests. You can still load this dataset in non-streaming mode by passing `streaming=False` (default)
Traceback: Traceback (most recent call last):
File "/src/workers/datasets_based/.venv/lib/python3.9/site-packages/datasets/download/streaming_download_manager.py", line 495, in xopen
file_obj = fsspec.open(file, mode=mode, *args, **kwargs).open()
File "/src/workers/datasets_based/.venv/lib/python3.9/site-packages/fsspec/core.py", line 419, in open
return open_files(
File "/src/workers/datasets_based/.venv/lib/python3.9/site-packages/fsspec/core.py", line 272, in open_files
fs, fs_token, paths = get_fs_token_paths(
File "/src/workers/datasets_based/.venv/lib/python3.9/site-packages/fsspec/core.py", line 586, in get_fs_token_paths
fs = filesystem(protocol, **inkwargs)
File "/src/workers/datasets_based/.venv/lib/python3.9/site-packages/fsspec/registry.py", line 252, in filesystem
return cls(**storage_options)
File "/src/workers/datasets_based/.venv/lib/python3.9/site-packages/fsspec/spec.py", line 76, in __call__
obj = super().__call__(*args, **kwargs)
File "/src/workers/datasets_based/.venv/lib/python3.9/site-packages/fsspec/implementations/zip.py", line 54, in __init__
self.zip = zipfile.ZipFile(self.fo, mode=mode)
File "/usr/local/lib/python3.9/zipfile.py", line 1266, in __init__
self._RealGetContents()
File "/usr/local/lib/python3.9/zipfile.py", line 1329, in _RealGetContents
endrec = _EndRecData(fp)
File "/usr/local/lib/python3.9/zipfile.py", line 263, in _EndRecData
fpin.seek(0, 2)
File "/src/workers/datasets_based/.venv/lib/python3.9/site-packages/fsspec/implementations/http.py", line 737, in seek
raise ValueError("Cannot seek streaming HTTP file")
ValueError: Cannot seek streaming HTTP file
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/src/workers/datasets_based/src/datasets_based/workers/first_rows.py", line 485, in compute_first_rows_response
rows = get_rows(
File "/src/workers/datasets_based/src/datasets_based/workers/first_rows.py", line 120, in decorator
return func(*args, **kwargs)
File "/src/workers/datasets_based/src/datasets_based/workers/first_rows.py", line 176, in get_rows
rows_plus_one = list(itertools.islice(ds, rows_max_number + 1))
File "/src/workers/datasets_based/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 917, in __iter__
for key, example in ex_iterable:
File "/src/workers/datasets_based/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 113, in __iter__
yield from self.generate_examples_fn(**self.kwargs)
File "/tmp/modules-cache/datasets_modules/datasets/tab_fact/bcae1c44400dec0f74f22bba297d6fe979e9751fb57d4e421f9d1676086c2985/tab_fact.py", line 126, in _generate_examples
with open(statements_file, encoding="utf-8") as f:
File "/src/workers/datasets_based/.venv/lib/python3.9/site-packages/datasets/streaming.py", line 70, in wrapper
return function(*args, use_auth_token=use_auth_token, **kwargs)
File "/src/workers/datasets_based/.venv/lib/python3.9/site-packages/datasets/download/streaming_download_manager.py", line 498, in xopen
raise NonStreamableDatasetError(
datasets.download.streaming_download_manager.NonStreamableDatasetError: Streaming is not possible for this dataset because data host server doesn't support HTTP range requests. You can still load this dataset in non-streaming mode by passing `streaming=False` (default)Need help to make the dataset viewer work? Open an discussion for direct support.
Dataset Card for TabFact
Dataset Summary
The problem of verifying whether a textual hypothesis holds the truth based on the given evidence, also known as fact verification, plays an important role in the study of natural language understanding and semantic representation. However, existing studies are restricted to dealing with unstructured textual evidence (e.g., sentences and passages, a pool of passages), while verification using structured forms of evidence, such as tables, graphs, and databases, remains unexplored. TABFACT is large scale dataset with 16k Wikipedia tables as evidence for 118k human annotated statements designed for fact verification with semi-structured evidence. The statements are labeled as either ENTAILED or REFUTED. TABFACT is challenging since it involves both soft linguistic reasoning and hard symbolic reasoning.
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Languages
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Dataset Structure
Data Instances
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Data Fields
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Data Splits
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Dataset Creation
Curation Rationale
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Source Data
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Initial Data Collection and Normalization
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Who are the source language producers?
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Annotations
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Annotation process
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Who are the annotators?
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Personal and Sensitive Information
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Considerations for Using the Data
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Other Known Limitations
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Additional Information
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Citation Information
@inproceedings{2019TabFactA,
title={TabFact : A Large-scale Dataset for Table-based Fact Verification},
author={Wenhu Chen, Hongmin Wang, Jianshu Chen, Yunkai Zhang, Hong Wang, Shiyang Li, Xiyou Zhou and William Yang Wang},
booktitle = {International Conference on Learning Representations (ICLR)},
address = {Addis Ababa, Ethiopia},
month = {April},
year = {2020}
}
Contributions
Thanks to @patil-suraj for adding this dataset.
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Homepage:
TabFact
Repository:
GitHub
Paper:
TabFact: A Large-scale Dataset for Table-based Fact Verification
Leaderboard:
Leaderboard
Point of Contact:
Wenhu Chen
