languages:
- en
paperswithcode_id: scitail
Dataset Card for "scitail"
Table of Contents
- Dataset Description
- Dataset Structure
- Dataset Creation
- Considerations for Using the Data
- Additional Information
Dataset Description
- Homepage: https://allenai.org/data/scitail
- Repository: More Information Needed
- Paper: More Information Needed
- Point of Contact: More Information Needed
- Size of downloaded dataset files: 54.07 MB
- Size of the generated dataset: 46.82 MB
- Total amount of disk used: 100.89 MB
Dataset Summary
The SciTail dataset is an entailment dataset created from multiple-choice science exams and web sentences. Each question and the correct answer choice are converted into an assertive statement to form the hypothesis. We use information retrieval to obtain relevant text from a large text corpus of web sentences, and use these sentences as a premise P. We crowdsource the annotation of such premise-hypothesis pair as supports (entails) or not (neutral), in order to create the SciTail dataset. The dataset contains 27,026 examples with 10,101 examples with entails label and 16,925 examples with neutral label
Supported Tasks and Leaderboards
Languages
Dataset Structure
We show detailed information for up to 5 configurations of the dataset.
Data Instances
dgem_format
- Size of downloaded dataset files: 13.52 MB
- Size of the generated dataset: 7.47 MB
- Total amount of disk used: 20.99 MB
An example of 'train' looks as follows.
predictor_format
- Size of downloaded dataset files: 13.52 MB
- Size of the generated dataset: 9.72 MB
- Total amount of disk used: 23.24 MB
An example of 'validation' looks as follows.
snli_format
- Size of downloaded dataset files: 13.52 MB
- Size of the generated dataset: 24.58 MB
- Total amount of disk used: 38.10 MB
An example of 'validation' looks as follows.
tsv_format
- Size of downloaded dataset files: 13.52 MB
- Size of the generated dataset: 5.05 MB
- Total amount of disk used: 18.56 MB
An example of 'validation' looks as follows.
Data Fields
The data fields are the same among all splits.
dgem_format
premise: astringfeature.hypothesis: astringfeature.label: astringfeature.hypothesis_graph_structure: astringfeature.
predictor_format
answer: astringfeature.sentence2_structure: astringfeature.sentence1: astringfeature.sentence2: astringfeature.gold_label: astringfeature.question: astringfeature.
snli_format
sentence1_binary_parse: astringfeature.sentence1_parse: astringfeature.sentence1: astringfeature.sentence2_parse: astringfeature.sentence2: astringfeature.annotator_labels: alistofstringfeatures.gold_label: astringfeature.
tsv_format
premise: astringfeature.hypothesis: astringfeature.label: astringfeature.
Data Splits
| name | train | validation | test |
|---|---|---|---|
| dgem_format | 23088 | 1304 | 2126 |
| predictor_format | 23587 | 1304 | 2126 |
| snli_format | 23596 | 1304 | 2126 |
| tsv_format | 23097 | 1304 | 2126 |
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{scitail,
Author = {Tushar Khot and Ashish Sabharwal and Peter Clark},
Booktitle = {AAAI},
Title = {{SciTail}: A Textual Entailment Dataset from Science Question Answering},
Year = {2018}
}
Contributions
Thanks to @patrickvonplaten, @mariamabarham, @lewtun, @thomwolf for adding this dataset.