/CommonGen

A Constrained Text Generation Challenge Towards Generative Commonsense Reasoning

Primary LanguagePythonMIT LicenseMIT

CommonGen: A Constrained Text Generation Challenge Towards Generative Commonsense Reasoning

@article{lin2019comgen,
    author = {Bill Yuchen Lin  and Wangchunshu Zhou and Ming Shen and Pei Zhou and Chandra Bhagavatula and Yejin Choi and Xiang Ren},
    title = {CommonGen: A Constrained Text Generation Challenge for Generative Commonsense Reasoning},
    journal = {Findings of EMNLP},
    year = {2020},
    note = {to appear}
}

CommonGen is a new constrained text generation dataset that requires different kinds of commonsense to generate sentences about everyday scenarios, and thus targets generative commonsense reasoning. This repo is for tracking the latest dataset, some baseline models and our evaluation scripts. Please check http://inklab.usc.edu/CommonGen/ for more details. Note that our arxiv article may contain some outdated statistics and information.

Content

  • dataset/final_data saves the latest version of the data. We may have updates on the dataset in the future. Please stay tuned.

  • methods shows some baseline methods with many frameworks such as OpenNMT and Fariseq, as well as UniLM.

  • evaluation contains the evaluation scripts for a variety of automatic metrics for testing the performance of system predictions against human-written results.

Contact

Feel free to directly email yuchen[dot]lin[at]usc[dot]edu if you have any feedback.