Update README.md

README.md

@@ -1,3 +1,101 @@
----
-license: cc0-1.0
----
+---
+license: cc0-1.0
+task_categories:
+- text-retrieval
+- summarization
+language:
+- en
+tags:
+- legal
+- law
+size_categories:
+- n<1K
+source_datasets:
+- https://huggingface.co/datasets/FiscalNote/billsum
+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: 500
+- config_name: corpus
+  features:
+  - name: _id
+    dtype: string
+  - name: title
+    dtype: string
+  - name: text
+    dtype: string
+  splits:
+  - name: corpus
+    num_examples: 500
+- config_name: queries
+  features:
+  - name: _id
+    dtype: string
+  - name: text
+    dtype: string
+  splits:
+  - name: queries
+    num_examples: 500
+configs:
+- config_name: default
+  data_files:
+  - split: test
+    path: data/default.jsonl
+- config_name: corpus
+  data_files:
+  - split: corpus
+    path: data/corpus.jsonl
+- config_name: queries
+  data_files:
+  - split: queries
+    path: data/queries.jsonl
+pretty_name: BillSum MTEB Benchmark
+---
+# BillSum MTEB Benchmark 🏋
+This is the [BillSum](https://huggingface.co/datasets/FiscalNote/billsum) dataset formatted in the [Massive Text Embedding Benchmark (MTEB)](https://github.com/embeddings-benchmark/mteb) information retrieval dataset format.
+
+This dataset is intended to facilitate the consistent and reproducible evaluation of summarization and information retrieval models on BillSum with the [`mteb`](https://github.com/embeddings-benchmark/mteb) embedding model evaluation framework.
+
+More specifically, this dataset tests the ability of information retrieval models to identify legislation given a prompts formatted as a summary.
+
+This dataset has been processed into the MTEB format by [Isaacus](https://isaacus.com/), a legal AI research company.
+
+## Methodology 🧪
+To understand how BillSum was created, refer to its [documentation](https://github.com/FiscalNote/BillSum).
+
+This dataset was formatted by assigning the summaries as queries (or anchors), and treating the `text` column as relevant (or positive) passages.
+
+## Structure 🗂️
+As per the MTEB information retrieval dataset format, this dataset comprises three splits, `default`, `corpus` and `queries`.
+
+The `default` split pairs summary (`query-id`) with the raw text of the bills (`corpus-id`), each pair having a `score` of 1.
+
+The `corpus` split contains extracts from congressional bills, with the `text` key containg the raw text and its id being stored in the `_id` key.
+
+The `queries` split contains the summaries, with the text of a query being stored in the `text` key and its id being stored in the `_id` key.
+
+## License 📜
+To the extent that any intellectual property rights reside in the contributions made by Isaacus in formatting and processing this dataset, Isaacus licenses those contributions under the same license terms as the source dataset. You are free to use this dataset without citing Isaacus.
+
+The source dataset is licensed under [CC0](https://creativecommons.org/public-domain/cc0/).
+
+## Citation 🔖
+```bibtex
+@inproceedings{Eidelman_2019,
+   title={BillSum: A Corpus for Automatic Summarization of US Legislation},
+   url={http://dx.doi.org/10.18653/v1/D19-5406},
+   DOI={10.18653/v1/d19-5406},
+   booktitle={Proceedings of the 2nd Workshop on New Frontiers in Summarization},
+   publisher={Association for Computational Linguistics},
+   author={Eidelman, Vladimir},
+   year={2019},
+   pages={48–56} }
+```