README.md

---
pretty_name: License TL;DR Retrieval
task_categories:
- text-retrieval
- summarization
tags:
- legal
- law
- contractual
- licenses
language:
- en
annotations_creators:
- found
language_creators:
- found
license: cc-by-3.0
size_categories:
- n<1K
dataset_info:
- config_name: default
  features:
  - name: query-id
    dtype: string
  - name: corpus-id
    dtype: string
  - name: score
    dtype: float64
  splits:
  - name: test
    num_examples: 65
- config_name: corpus
  features:
  - name: _id
    dtype: string
  - name: title
    dtype: string
  - name: text
    dtype: string
  splits:
  - name: corpus
    num_examples: 65
- config_name: queries
  features:
  - name: _id
    dtype: string
  - name: text
    dtype: string
  splits:
  - name: queries
    num_examples: 65
configs:
- config_name: default
  data_files:
  - split: test
    path: default.jsonl
- config_name: corpus
  data_files:
  - split: corpus
    path: corpus.jsonl
- config_name: queries
  data_files:
  - split: queries
    path: queries.jsonl
---
# License TL;DR Retrieval 📑
**License TL;DR Retrieval** by [Isaacus](https://isaacus.com/) is a challenging legal information retrieval evaluation dataset consisting of 65 summary-license pairs sourced from [tl;drLegal](https://www.tldrlegal.com/).

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)](https://isaacus.com/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`](https://github.com/embeddings-benchmark/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](https://www.tldrlegal.com/) and pairing their human-created summaries with their full texts.

## License 📜
This dataset is licensed under [CC BY 3.0](https://creativecommons.org/licenses/by/3.0/legalcode) 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)](https://arxiv.org/abs/2510.19365):
```bibtex
@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}, 
}
```