---
# System prepended metadata

title: CommonGen

---


# CommonGen

## Summary
* [Introduction](#introduction)
* [Dataset Structure](#dataset-structure)
* [Reference](#reference)
* [License](#license)
* [Citation](#citation)

## Introduction
CommonGen is a constrained text generation task, associated with a benchmark dataset, to explicitly test machines for the ability of generative commonsense reasoning. Given a set of common concepts; the task is to generate a coherent sentence describing an everyday scenario using these concepts.

![](https://s3.w3s.aioz.network/w3ai-platform-v2/uploads/samples/54deb202-59ab-491b-b167-e0d95f9c4eb7/2024/07/12/1720774926-aaRmW5YyYH95dSghngnmwB.png?AWSAccessKeyId=FT7EO3IGQNMIILHXIDZRVTJHWE&Signature=0ipUGsFgKn36ZhK%2FWs1jtq48Ks0%3D&Expires=2351494926) 

CommonGen is challenging because it inherently requires 1) relational reasoning using background commonsense knowledge, and 2) compositional generalization ability to work on unseen concept combinations. Our dataset, constructed through a combination of crowd-sourcing from AMT and existing caption corpora, consists of 30k concept-sets and 50k sentences in total.
## Dataset Structure

### Data Instances
* **Size of downloaded dataset files**: 1.85 MB
* **Size of the generated dataset**: 7.21 MB
* **Total amount of disk used**: 9.06 MB

An example of 'train' looks as follows.
```
{
    "concept_set_idx": 0,
    "concepts": ["ski", "mountain", "skier"],
    "target": "Three skiers are skiing on a snowy mountain."
}
```
### Data Fields
The data fields are the same among all splits.
* `concept_set_idx`: a int32 feature.
* `concepts`: a list of string features.
* `target`: a string feature.

### Data Splits



|  name   | train | validation | test |
|:-------:|:-----:|:----------:|:----:|
| default | 67389 |    4018    | 1497 |



## Reference

We would like to acknowledge Lin, Bill Yuchen et al. for creating and maintaining the CommonGen dataset as a valuable resource for the computer vision and machine learning research community. For more information about the CommonGen dataset and its creator, please visit [the CommonGen website](https://inklab.usc.edu/CommonGen/index.html).


## License 

The dataset has been released under the MIT License.
## Citation
```
@inproceedings{lin-etal-2020-commongen,
    title = "{C}ommon{G}en: A Constrained Text Generation Challenge for Generative Commonsense Reasoning",
    author = "Lin, Bill Yuchen  and
      Zhou, Wangchunshu  and
      Shen, Ming  and
      Zhou, Pei  and
      Bhagavatula, Chandra  and
      Choi, Yejin  and
      Ren, Xiang",
    booktitle = "Findings of the Association for Computational Linguistics: EMNLP 2020",
    month = nov,
    year = "2020",
    address = "Online",
    publisher = "Association for Computational Linguistics",
    url = "https://www.aclweb.org/anthology/2020.findings-emnlp.165",
    doi = "10.18653/v1/2020.findings-emnlp.165",
    pages = "1823--1840"
}
```
