|
--- |
|
annotations_creators: |
|
- expert-generated |
|
language: |
|
- en |
|
language_creators: |
|
- found |
|
license: |
|
- odc-by |
|
multilinguality: |
|
- monolingual |
|
pretty_name: Multi-LexSum |
|
size_categories: |
|
- 1K<n<10K |
|
- 10K<n<100K |
|
source_datasets: |
|
- original |
|
tags: [] |
|
task_categories: |
|
- summarization |
|
task_ids: [] |
|
--- |
|
|
|
# Dataset Card for Multi-LexSum |
|
## Table of Contents |
|
- [Dataset Card for Multi-LexSum](#dataset-card-for-multi-lexsum) |
|
- [Table of Contents](#table-of-contents) |
|
- [Dataset Description](#dataset-description) |
|
- [Dataset Summary](#dataset-summary) |
|
- [Languages](#languages) |
|
- [Dataset](#dataset) |
|
- [Data Fields](#data-fields) |
|
- [Data Splits](#data-splits) |
|
- [Dataset Sheet (Datasheet)](#dataset-sheet-datasheet) |
|
- [Additional Information](#additional-information) |
|
- [Dataset Curators](#dataset-curators) |
|
- [Licensing Information](#licensing-information) |
|
- [Citation Information](#citation-information) |
|
- [Release History](#release-history) |
|
|
|
## Dataset Description |
|
|
|
- **Homepage:** https://multilexsum.github.io |
|
- **Repository:** https://github.com/multilexsum/dataset |
|
- **Paper:** https://arxiv.org/abs/2206.10883 |
|
|
|
<p> |
|
<a href="https://multilexsum.github.io" style="display: inline-block;"> |
|
<img src="https://img.shields.io/badge/-homepage-informational.svg?logo=jekyll" title="Multi-LexSum Paper" style="margin-top: 0.25rem; margin-bottom: 0.25rem"></a> |
|
<a href="https://github.com/multilexsum/dataset" style="display: inline-block;"> |
|
<img src="https://img.shields.io/badge/-multilexsum-lightgrey.svg?logo=github" title="Multi-LexSum Github Repo" style="margin-top: 0.25rem; margin-bottom: 0.25rem"></a> |
|
<a href="https://arxiv.org/abs/2206.10883" style="display: inline-block;"> |
|
<img src="https://img.shields.io/badge/NeurIPS-2022-9cf" title="Multi-LexSum is accepted in NeurIPS 2022" style="margin-top: 0.25rem; margin-bottom: 0.25rem"></a> |
|
</p> |
|
|
|
### Talk @ NeurIPS 2022 |
|
|
|
[](https://youtu.be/C-fwW_ZhkE8) |
|
|
|
|
|
### Dataset Summary |
|
|
|
The Multi-LexSum dataset is a collection of 9,280 such legal case summaries. Multi-LexSum is distinct from other datasets in its **multiple target summaries, each at a different granularity** (ranging from one-sentence “extreme” summaries to multi-paragraph narrations of over five hundred words). It presents a challenging multi-document summarization task given **the long length of the source documents**, often exceeding two hundred pages per case. Unlike other summarization datasets that are (semi-)automatically curated, Multi-LexSum consists of **expert-authored summaries**: the experts—lawyers and law students—are trained to follow carefully created guidelines, and their work is reviewed by an additional expert to ensure quality. |
|
|
|
### Languages |
|
|
|
English |
|
|
|
## Dataset |
|
|
|
### Data Fields |
|
|
|
The dataset contains a list of instances (cases); each instance contains the following data: |
|
|
|
| Field | Description | |
|
| ------------: | -------------------------------------------------------------------------------: | |
|
| id | `(str)` The case ID | |
|
| sources | `(List[str])` A list of strings for the text extracted from the source documents | |
|
| summary/long | `(str)` The long (multi-paragraph) summary for this case | |
|
| summary/short | `(Optional[str])` The short (one-paragraph) summary for this case | |
|
| summary/tiny | `(Optional[str])` The tiny (one-sentence) summary for this case | |
|
|
|
Please check the exemplar usage below for loading the data: |
|
|
|
```python |
|
from datasets import load_dataset |
|
|
|
multi_lexsum = load_dataset("allenai/multi_lexsum", name="v20230518") |
|
# Download multi_lexsum locally and load it as a Dataset object |
|
|
|
example = multi_lexsum["validation"][0] # The first instance of the dev set |
|
example["sources"] # A list of source document text for the case |
|
|
|
for sum_len in ["long", "short", "tiny"]: |
|
print(example["summary/" + sum_len]) # Summaries of three lengths |
|
|
|
print(example['case_metadata']) # The corresponding metadata for a case in a dict |
|
``` |
|
|
|
### Data Splits |
|
|
|
| | Instances | Source Documents (D) | Long Summaries (L) | Short Summaries (S) | Tiny Summaries (T) | Total Summaries | |
|
| ----------: | --------: | -------------------: | -----------------: | ------------------: | -----------------: | --------------: | |
|
| Train (70%) | 3,177 | 28,557 | 3,177 | 2,210 | 1,130 | 6,517 | |
|
| Test (20%) | 908 | 7,428 | 908 | 616 | 312 | 1,836 | |
|
| Dev (10%) | 454 | 4,134 | 454 | 312 | 161 | 927 | |
|
|
|
|
|
## Dataset Sheet (Datasheet) |
|
|
|
Please check our [dataset sheet](https://multilexsum.github.io/datasheet) for details regarding dataset creation, source data, annotation, and considerations for the usage. |
|
|
|
## Additional Information |
|
|
|
### Dataset Curators |
|
|
|
The dataset is created by the collaboration between Civil Rights Litigation Clearinghouse (CRLC, from University of Michigan) and Allen Institute for AI. Multi-LexSum builds on the dataset used and posted by the Clearinghouse to inform the public about civil rights litigation. |
|
|
|
### Licensing Information |
|
|
|
The Multi-LexSum dataset is distributed under the [Open Data Commons Attribution License (ODC-By)](https://opendatacommons.org/licenses/by/1-0/). |
|
The case summaries and metadata are licensed under the [Creative Commons Attribution License (CC BY-NC)](https://creativecommons.org/licenses/by-nc/4.0/), and the source documents are already in the public domain. |
|
Commercial users who desire a license for summaries and metadata can contact [info@clearinghouse.net](mailto:info@clearinghouse.net), which will allow free use but limit summary re-posting. |
|
The corresponding code for downloading and loading the dataset is licensed under the Apache License 2.0. |
|
|
|
### Citation Information |
|
|
|
|
|
``` |
|
@article{Shen2022MultiLexSum, |
|
author = {Zejiang Shen and |
|
Kyle Lo and |
|
Lauren Yu and |
|
Nathan Dahlberg and |
|
Margo Schlanger and |
|
Doug Downey}, |
|
title = {Multi-LexSum: Real-World Summaries of Civil Rights Lawsuits at Multiple Granularities}, |
|
journal = {CoRR}, |
|
volume = {abs/2206.10883}, |
|
year = {2022},**** |
|
url = {https://doi.org/10.48550/arXiv.2206.10883}, |
|
doi = {10.48550/arXiv.2206.10883} |
|
} |
|
``` |
|
|
|
|
|
## Release History |
|
|
|
| Version | Description | |
|
| ----------: | -----------------------------------------------------------: | |
|
| `v20230518` | The v1.1 release including case and source document metadata | |
|
| `v20220616` | The initial v1.0 release | |
