# scitail by Ai2: AI Training Dataset
Source: https://savrn.com/datasets/scitail
Markdown alternate of the page above; the site index is https://savrn.com/llms.txt

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## Dataset Card

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 An example of 'train' looks as follows. An example of 'validation' looks as follows. An…

Excerpt from the card by Ai2.

## Structure

### dgem_format 26,518 rows

| Split | Rows | Size |
| --- | --- | --- |
| train | 23,088 | 7.4 MB |
| test | 2,126 | 588.1 KB |
| validation | 1,304 | 378.0 KB |

premisestringhypothesisstringlabelstringhypothesis_graph_structurestring

### predictor_format 27,017 rows

| Split | Rows | Size |
| --- | --- | --- |
| train | 23,587 | 9.1 MB |
| test | 2,126 | 769.1 KB |
| validation | 1,304 | 487.2 KB |

answerstringsentence2_structurestringsentence1stringsentence2stringgold_labelstringquestionstring

### snli_format 27,026 rows

| Split | Rows | Size |
| --- | --- | --- |
| train | 23,596 | 23.0 MB |
| test | 2,126 | 2.0 MB |
| validation | 1,304 | 1.2 MB |

sentence1_binary_parsestringsentence1_parsestringsentence1stringsentence2_parsestringsentence2stringannotator_labelsSequencegold_labelstring

### tsv_format 26,527 rows

| Split | Rows | Size |
| --- | --- | --- |
| train | 23,097 | 5.0 MB |
| test | 2,126 | 409.1 KB |
| validation | 1,304 | 251.9 KB |

premisestringhypothesisstringlabelstring

## Details

Repository

allenai/scitail

Publisher

Ai2

Task category

Not stated by the source

Tags

Not stated by the source

Size category

Not stated by the source

Languages

en

Revision

0cc4353235b289165dfde1c7c5d1be983f99ce44

Last updated

2024-01-04

## Files

14 files, 13.5 MB in total.

Data12 files · 13.5 MB

Documentation1 file · 10.1 KB

Repository1 file · 1.2 KB

Every file

| File | Type | Size | SHA-256 |
| --- | --- | --- | --- |
| dgem_format/test-00000-of-00001.parquet | Data | 185.0 KB | 56dbd29881d1 |
| dgem_format/train-00000-of-00001.parquet | Data | 1.7 MB | 0d2a8a30dbc7 |
| dgem_format/validation-00000-of-00001.parquet | Data | 112.3 KB | de818ba1a5ee |
| predictor_format/test-00000-of-00001.parquet | Data | 210.2 KB | 5e9a9018642c |
| predictor_format/train-00000-of-00001.parquet | Data | 1.8 MB | f50f8d853224 |
| predictor_format/validation-00000-of-00001.parquet | Data | 125.2 KB | 0e101a3ddfb1 |
| snli_format/test-00000-of-00001.parquet | Data | 653.1 KB | 9814bcb18de3 |
| snli_format/train-00000-of-00001.parquet | Data | 6.4 MB | c4c77597d52d |
| snli_format/validation-00000-of-00001.parquet | Data | 400.3 KB | cfcbb30a8c37 |
| tsv_format/test-00000-of-00001.parquet | Data | 162.2 KB | c2b4b8b5e258 |
| tsv_format/train-00000-of-00001.parquet | Data | 1.6 MB | 35ffcef823e4 |
| tsv_format/validation-00000-of-00001.parquet | Data | 99.8 KB | 7342d7d9c3f0 |
| README.md | Documentation | 10.1 KB | — |
| .gitattributes | Repository | 1.2 KB | — |

## License and Download

License

Not stated by the source

Access

No access gate

[Download from Ai2](https://huggingface.co/datasets/allenai/scitail)

Released by Ai2 through its official repository on Hugging Face.

## Ai2

[All models and datasets](https://savrn.com/model-publishers/allenai)

## Explore More

- [The dataset directory](https://savrn.com/datasets)
- [The model directory](https://savrn.com/models)
- [Research papers](https://savrn.com/papers)

## Source

- Repository metadata, read 2026-10-19.
- [Ai2 website](https://allenai.org/)
- [Hugging Face record](https://huggingface.co/datasets/allenai/scitail)
- [How the hub is built](https://savrn.com/model-hub/methodology)
