Dataset Summary

New dataset introduced in Parameter-Efficient Legal Domain Adaptation (Li et al., 2022) from the Legal Advice Reddit community (known as "/r/legaldvice"), sourcing the Reddit posts from the Pushshift Reddit dataset. The dataset maps the text and title of each legal question posted into one of eleven classes, based on the original Reddit post's "flair" (i.e., tag). Questions are typically informal and use non-legal-specific language. Per the Legal Advice Reddit rules, posts must be about actual personal circumstances or situations. We limit the number of labels to the top eleven classes and remove the other samples from the dataset.

Citation Information

@inproceedings{li-etal-2022-parameter,
    title = "Parameter-Efficient Legal Domain Adaptation",
    author = "Li, Jonathan  and
      Bhambhoria, Rohan  and
      Zhu, Xiaodan",
    booktitle = "Proceedings of the Natural Legal Language Processing Workshop 2022",
    month = dec,
    year = "2022",
    address = "Abu Dhabi, United Arab Emirates (Hybrid)",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2022.nllp-1.10",
    pages = "119--129",
}