
# Dataset Card for "hans"

## Table of Contents
- [Dataset Description](#dataset-description)
  - [Dataset Summary](#dataset-summary)
  - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
  - [Languages](#languages)
- [Dataset Structure](#dataset-structure)
  - [Data Instances](#data-instances)
  - [Data Fields](#data-fields)
  - [Data Splits](#data-splits)
- [Dataset Creation](#dataset-creation)
  - [Curation Rationale](#curation-rationale)
  - [Source Data](#source-data)
  - [Annotations](#annotations)
  - [Personal and Sensitive Information](#personal-and-sensitive-information)
- [Considerations for Using the Data](#considerations-for-using-the-data)
  - [Social Impact of Dataset](#social-impact-of-dataset)
  - [Discussion of Biases](#discussion-of-biases)
  - [Other Known Limitations](#other-known-limitations)
- [Additional Information](#additional-information)
  - [Dataset Curators](#dataset-curators)
  - [Licensing Information](#licensing-information)
  - [Citation Information](#citation-information)
  - [Contributions](#contributions)

## Dataset Description

- **Homepage:** [https://github.com/tommccoy1/hans](https://github.com/tommccoy1/hans)
- **Repository:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
- **Paper:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
- **Point of Contact:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
- **Size of downloaded dataset files:** 30.94 MB
- **Size of the generated dataset:** 31.81 MB
- **Total amount of disk used:** 62.76 MB

### Dataset Summary

The HANS dataset is an NLI evaluation set that tests specific hypotheses about invalid heuristics that NLI models are likely to learn.

### Supported Tasks and Leaderboards

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Languages

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

## Dataset Structure

### Data Instances

#### plain_text

- **Size of downloaded dataset files:** 30.94 MB
- **Size of the generated dataset:** 31.81 MB
- **Total amount of disk used:** 62.76 MB

An example of 'train' looks as follows.
```

```

### Data Fields

The data fields are the same among all splits.

#### plain_text
- `premise`: a `string` feature.
- `hypothesis`: a `string` feature.
- `label`: a classification label, with possible values including `entailment` (0), `non-entailment` (1).
- `parse_premise`: a `string` feature.
- `parse_hypothesis`: a `string` feature.
- `binary_parse_premise`: a `string` feature.
- `binary_parse_hypothesis`: a `string` feature.
- `heuristic`: a `string` feature.
- `subcase`: a `string` feature.
- `template`: a `string` feature.

### Data Splits

|   name   |train|validation|
|----------|----:|---------:|
|plain_text|30000|     30000|

## Dataset Creation

### Curation Rationale

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Source Data

#### Initial Data Collection and Normalization

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

#### Who are the source language producers?

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Annotations

#### Annotation process

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

#### Who are the annotators?

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Personal and Sensitive Information

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

## Considerations for Using the Data

### Social Impact of Dataset

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Discussion of Biases

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Other Known Limitations

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

## Additional Information

### Dataset Curators

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Licensing Information

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Citation Information

```
@article{DBLP:journals/corr/abs-1902-01007,
  author    = {R. Thomas McCoy and
               Ellie Pavlick and
               Tal Linzen},
  title     = {Right for the Wrong Reasons: Diagnosing Syntactic Heuristics in Natural
               Language Inference},
  journal   = {CoRR},
  volume    = {abs/1902.01007},
  year      = {2019},
  url       = {http://arxiv.org/abs/1902.01007},
  archivePrefix = {arXiv},
  eprint    = {1902.01007},
  timestamp = {Tue, 21 May 2019 18:03:36 +0200},
  biburl    = {https://dblp.org/rec/journals/corr/abs-1902-01007.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

```


### Contributions

Thanks to [@TevenLeScao](https://github.com/TevenLeScao), [@thomwolf](https://github.com/thomwolf) for adding this dataset.
task_categories:text-classification task_ids:natural-language-inference annotations_creators:expert-generated language_creators:expert-generated multilinguality:monolingual size_categories:10K<n<100K source_datasets:original language:en license:unknown arxiv:1902.01007 region:us
{"annotations_creators": ["expert-generated"], "language_creators": ["expert-generated"], "language": ["en"], "license": ["unknown"], "multilinguality": ["monolingual"], "size_categories": ["10K<n<100K"], "source_datasets": ["original"], "task_categories": ["text-classification"], "task_ids": ["natural-language-inference"], "paperswithcode_id": "hans", "pretty_name": "Heuristic Analysis for NLI Systems", "dataset_info": {"features": [{"name": "premise", "dtype": "string"}, {"name": "hypothesis", "dtype": "string"}, {"name": "label", "dtype": {"class_label": {"names": {"0": "entailment", "1": "non-entailment"}}}}, {"name": "parse_premise", "dtype": "string"}, {"name": "parse_hypothesis", "dtype": "string"}, {"name": "binary_parse_premise", "dtype": "string"}, {"name": "binary_parse_hypothesis", "dtype": "string"}, {"name": "heuristic", "dtype": "string"}, {"name": "subcase", "dtype": "string"}, {"name": "template", "dtype": "string"}], "config_name": "plain_text", "splits": [{"name": "train", "num_bytes": 15916371, "num_examples": 30000}, {"name": "validation", "num_bytes": 15893137, "num_examples": 30000}], "download_size": 30947358, "dataset_size": 31809508}}
TAGS
#task_categories-text-classification #task_ids-natural-language-inference #annotations_creators-expert-generated #language_creators-expert-generated #multilinguality-monolingual #size_categories-10K<n<100K #source_datasets-original #language-English #license-unknown #arxiv-1902.01007 #region-us 

Dataset Card for "hans"
=======================


Table of Contents
-----------------


* Dataset Description
	+ Dataset Summary
	+ Supported Tasks and Leaderboards
	+ Languages
* Dataset Structure
	+ Data Instances
	+ Data Fields
	+ Data Splits
* Dataset Creation
	+ Curation Rationale
	+ Source Data
	+ Annotations
	+ 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
	+ Contributions


Dataset Description
-------------------


* Homepage: URL
* Repository:
* Paper:
* Point of Contact:
* Size of downloaded dataset files: 30.94 MB
* Size of the generated dataset: 31.81 MB
* Total amount of disk used: 62.76 MB


### Dataset Summary


The HANS dataset is an NLI evaluation set that tests specific hypotheses about invalid heuristics that NLI models are likely to learn.


### Supported Tasks and Leaderboards


### Languages


Dataset Structure
-----------------


### Data Instances


#### plain\_text


* Size of downloaded dataset files: 30.94 MB
* Size of the generated dataset: 31.81 MB
* Total amount of disk used: 62.76 MB


An example of 'train' looks as follows.


### Data Fields


The data fields are the same among all splits.


#### plain\_text


* 'premise': a 'string' feature.
* 'hypothesis': a 'string' feature.
* 'label': a classification label, with possible values including 'entailment' (0), 'non-entailment' (1).
* 'parse\_premise': a 'string' feature.
* 'parse\_hypothesis': a 'string' feature.
* 'binary\_parse\_premise': a 'string' feature.
* 'binary\_parse\_hypothesis': a 'string' feature.
* 'heuristic': a 'string' feature.
* 'subcase': a 'string' feature.
* 'template': a 'string' feature.


### Data Splits



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


### Contributions


Thanks to @TevenLeScao, @thomwolf for adding this dataset.



### Dataset Summary


The HANS dataset is an NLI evaluation set that tests specific hypotheses about invalid heuristics that NLI models are likely to learn. ### Supported Tasks and Leaderboards ### Languages


Dataset Structure
----------------- ### Data Instances #### plain\_text


* Size of downloaded dataset files: 30.94 MB
* Size of the generated dataset: 31.81 MB
* Total amount of disk used: 62.76 MB


An example of 'train' looks as follows. ### Data Fields


The data fields are the same among all splits. #### plain\_text


* 'premise': a 'string' feature.
* 'hypothesis': a 'string' feature.
* 'label': a classification label, with possible values including 'entailment' (0), 'non-entailment' (1).
* 'parse\_premise': a 'string' feature.
* 'parse\_hypothesis': a 'string' feature.
* 'binary\_parse\_premise': a 'string' feature.
* 'binary\_parse\_hypothesis': a 'string' feature.
* 'heuristic': a 'string' feature.
* 'subcase': a 'string' feature.
* 'template': a 'string' feature. ### Data Splits



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 ### Contributions


Thanks to @TevenLeScao, @thomwolf for adding this dataset.
TAGS
#task_categories-text-classification #task_ids-natural-language-inference #annotations_creators-expert-generated #language_creators-expert-generated #multilinguality-monolingual #size_categories-10K<n<100K #source_datasets-original #language-English #license-unknown #arxiv-1902.01007 #region-us 
 ### Dataset Summary


The HANS dataset is an NLI evaluation set that tests specific hypotheses about invalid heuristics that NLI models are likely to learn. ### Supported Tasks and Leaderboards ### Languages


Dataset Structure
----------------- ### Data Instances #### plain\_text


* Size of downloaded dataset files: 30.94 MB
* Size of the generated dataset: 31.81 MB
* Total amount of disk used: 62.76 MB


An example of 'train' looks as follows. ### Data Fields


The data fields are the same among all splits. #### plain\_text


* 'premise': a 'string' feature.
* 'hypothesis': a 'string' feature.
* 'label': a classification label, with possible values including 'entailment' (0), 'non-entailment' (1).
* 'parse\_premise': a 'string' feature.
* 'parse\_hypothesis': a 'string' feature.
* 'binary\_parse\_premise': a 'string' feature.
* 'binary\_parse\_hypothesis': a 'string' feature.
* 'heuristic': a 'string' feature.
* 'subcase': a 'string' feature.
* 'template': a 'string' feature. ### Data Splits



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 ### Contributions


Thanks to @TevenLeScao, @thomwolf for adding this dataset.
passage: TAGS
#task_categories-text-classification #task_ids-natural-language-inference #annotations_creators-expert-generated #language_creators-expert-generated #multilinguality-monolingual #size_categories-10K<n<100K #source_datasets-original #language-English #license-unknown #arxiv-1902.01007 #region-us 
### Dataset Summary


The HANS dataset is an NLI evaluation set that tests specific hypotheses about invalid heuristics that NLI models are likely to learn.### Supported Tasks and Leaderboards### Languages


Dataset Structure
-----------------### Data Instances#### plain\_text


* Size of downloaded dataset files: 30.94 MB
* Size of the generated dataset: 31.81 MB
* Total amount of disk used: 62.76 MB


An example of 'train' looks as follows.### Data Fields


The data fields are the same among all splits.#### plain\_text


* 'premise': a 'string' feature.
* 'hypothesis': a 'string' feature.
* 'label': a classification label, with possible values including 'entailment' (0), 'non-entailment' (1).
* 'parse\_premise': a 'string' feature.
* 'parse\_hypothesis': a 'string' feature.
* 'binary\_parse\_premise': a 'string' feature.
* 'binary\_parse\_hypothesis': a 'string' feature.
* 'heuristic': a 'string' feature.
* 'subcase': a 'string' feature.
* 'template': a 'string' feature.### Data Splits



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