isaacus/license-tldr-retrieval

License TL;DR Retrieval 📑

License TL;DR Retrieval by Isaacus is a challenging legal information retrieval evaluation dataset consisting of 65 summary-license pairs sourced from tl;drLegal.

This dataset is intended to stress test the ability of an information retrieval model to match relevant open source licenses with summaries of their terms.

This dataset forms part of the Massive Legal Embeddings Benchmark (MLEB), the largest, most diverse, and most comprehensive benchmark for legal text embedding models.

Structure 🗂️

As per the MTEB information retrieval dataset format, this dataset comprises three splits, default, corpus and queries.

The default split pairs summaries (query-id) with licenses (corpus-id), each pair having a score of 1.

The corpus split contains licenses from tl;drLegal, with their full texts being stored in the text key and their ids being stored in the _id key. There is also a title column which is deliberately set to an empty string in all cases for compatibility with the mteb library.

The queries split contains summaries of licenses, with the text of summaries being stored in the text key and their ids being stored in the _id key.

Methodology 🧪

This dataset was constructed by collecting all licenses available on tl;drLegal and pairing their human-created summaries with their full texts.

License 📜

This dataset is licensed under CC BY 3.0 which allows for both non-commercial and commercial use of this dataset as long as appropriate attribution is made to it.

Citation 🔖

If you use this dataset, please cite the Massive Legal Embeddings Benchmark (MLEB):

@misc{butler2025massivelegalembeddingbenchmark,
      title={The Massive Legal Embedding Benchmark (MLEB)}, 
      author={Umar Butler and Abdur-Rahman Butler and Adrian Lucas Malec},
      year={2025},
      eprint={2510.19365},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2510.19365}, 
}