README.md

---
annotations_creators:
- crowdsourced
language_creators:
- crowdsourced
language:
- en
license:
- mit
multilinguality:
- monolingual
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- question-answering
task_ids:
- open-domain-qa
paperswithcode_id: commonsenseqa
pretty_name: CommonsenseQA
dataset_info:
  features:
  - name: id
    dtype: string
  - name: question
    dtype: string
  - name: question_concept
    dtype: string
  - name: choices
    sequence:
    - name: label
      dtype: string
    - name: text
      dtype: string
  - name: answerKey
    dtype: string
  splits:
  - name: train
    num_bytes: 2207794
    num_examples: 9741
  - name: validation
    num_bytes: 273848
    num_examples: 1221
  - name: test
    num_bytes: 257842
    num_examples: 1140
  download_size: 1558570
  dataset_size: 2739484
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
  - split: validation
    path: data/validation-*
  - split: test
    path: data/test-*
---

## Usage

```python
from datasets import load_dataset

dataset=load_dataset(
	"Sadanto3933/commonsense_qa",
	split="train",
	)

# ...
```

# Dataset Card for "commonsense_qa"

## Dataset Description

- **Homepage:** https://www.tau-nlp.org/commonsenseqa
- **Repository:** https://github.com/jonathanherzig/commonsenseqa
- **Paper:** https://arxiv.org/abs/1811.00937
- **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:** 4.68 MB
- **Size of the generated dataset:** 2.18 MB
- **Total amount of disk used:** 6.86 MB

### Dataset Summary

CommonsenseQA is a new multiple-choice question answering dataset that requires different types of commonsense knowledge
to predict the correct answers. 
The dataset is provided in two major training/validation/testing set splits: "Random split" which is the main evaluation
split, and "Question token split", see paper for details.

### Supported Tasks and Leaderboards

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

### Languages

The dataset is in English (`en`).

## Dataset Structure

### Data Instances


An example of 'train' looks as follows:
```json
{'id': '075e483d21c29a511267ef62bedc0461',
 'question': 'The sanctions against the school were a punishing blow, and they seemed to what the efforts the school had made to change?',
 'question_concept': 'punishing',
 'choices': {'label': ['A', 'B', 'C', 'D', 'E'],
  'text': ['ignore', 'enforce', 'authoritarian', 'yell at', 'avoid']},
 'answerKey': 'A'}
```

### Data Fields

The data fields are the same among all splits.

#### default
- `id` (`str`): Unique ID.
- `question`: a `string` feature.
- `question_concept` (`str`): ConceptNet concept associated to the question.
- `choices`: a dictionary feature containing:
  - `label`: a `string` feature.
  - `text`: a `string` feature.
- `answerKey`: a `string` feature.

## Dataset Creation


### Licensing Information

The dataset is licensed under the MIT License.

See: https://github.com/jonathanherzig/commonsenseqa/issues/5

### Citation Information

```
@inproceedings{talmor-etal-2019-commonsenseqa,
    title = "{C}ommonsense{QA}: A Question Answering Challenge Targeting Commonsense Knowledge",
    author = "Talmor, Alon  and
      Herzig, Jonathan  and
      Lourie, Nicholas  and
      Berant, Jonathan",
    booktitle = "Proceedings of the 2019 Conference of the North {A}merican Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers)",
    month = jun,
    year = "2019",
    address = "Minneapolis, Minnesota",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/N19-1421",
    doi = "10.18653/v1/N19-1421",
    pages = "4149--4158",
    archivePrefix = "arXiv",
    eprint        = "1811.00937",
    primaryClass  = "cs",
}
```