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GitHub - thunlp/LEVEN: Source code and dataset for ACL2022 Findings Paper "LEVEN: A Large-Scale Chinese Legal Event Detection dataset"
GitHub - thunlp/LEVEN: Source code and dataset for ACL2022 Findings Paper "LEVEN: A Large-Scale Chinese Legal Event Detection dataset"
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Source code and dataset for ACL2022 Findings Paper "LEVEN: A Large-Scale Chinese Legal Event Detection dataset"
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thunlp/LEVEN
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mainBranchesTagsGo to fileCodeFolders and filesNameNameLast commit messageLast commit dateLatest commit History17 CommitsAnnotation-GuidelinesAnnotation-Guidelines BaselinesBaselines DownstreamsDownstreams picpic posterposter .DS_Store.DS_Store README.mdREADME.md evaluate.pyevaluate.py View all filesRepository files navigationREADMELEVEN
Dataset and source code for ACL 2022 Findings paper "LEVEN: A Large-Scale Chinese Legal Event Detection Dataset" .
Background
Events are the essence of the facts in legal cases. Therefore, Legal Event Detection (LED) is fundamentally important and naturally beneficial to case understanding and other Legal AI tasks.
Overview
The dataset can be obtained from Tsinghua Cloud or Google Drive. The annotation guidelines are provided in Annotation Guidelines.
You can also check out our poster at ACL2022 main conference.
We remove the annotations for the test set deliberately. To get the results on LEVEN test set, please refer to Leaderboard.
Large Scale
LEVEN is the largest Legal Event Detection dataset and the largest Chinese Event Detection dataset. Here is a comparison between the scale of LEVEN and other datasets.
Datasets denoted with * are not publicly available, and – means the value is not accessible
High Coverage
LEVEN contains 108 event types in total, including 64 charge-oriented events and 44 general events. Their distribution is shown below.
The LEVEN event schema has a sophisticated hierarchical structure, which is shown here.
Leaderboard
LEVEN is adopted for CAIL 2022, the most influential Legal AI contest in China.
You can submit your predictions to CAIL Event Detection Track to win a prize up to CNY 15,000!
Please follow submission instructions here.
Experiments
The source codes for the experiments are included in the Baselines and Downstreams folder.
The Baselines folder includes DMCNN, BiLSTM, BiLSTM+CRF, BERT, BERT+CRF and DMBERT.
The Downstreams folder includes Legal Judgment Prediction and Similar Case Retrieval.
Baselines
We implement six competitive Baselines and their performances are as follows.
Downstream Tasks
We also explore the use of LEVEN on two Downstreams. We simply use event as side information to promote the performance of Legal Judgment Prediction and Similar Case Retrieval.
The experiment results for Legal Judgment Prediction are shown below.
The experiment results for Similar Case Retrieval are shown below.
Schema
The Chinese event schema is shown below. Please check our paper for the English version.
The detailed explanation and annotation guidelines are provided in Annotation Guidelines.
Citation
If these data and codes help you, please cite this paper.
@inproceedings{yao-etal-2022-leven,
title = "{LEVEN}: A Large-Scale {C}hinese Legal Event Detection Dataset",
author = "Yao, Feng and Xiao, Chaojun and Wang, Xiaozhi and Liu, Zhiyuan and Hou, Lei and Tu, Cunchao and Li, Juanzi and Liu, Yun and Shen, Weixing and Sun, Maosong",
booktitle = "Findings of the Association for Computational Linguistics: ACL 2022",
year = "2022",
url = "https://aclanthology.org/2022.findings-acl.17",
doi = "10.18653/v1/2022.findings-acl.17",
pages = "183--201",
}
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Source code and dataset for ACL2022 Findings Paper "LEVEN: A Large-Scale Chinese Legal Event Detection dataset"
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[2203.08556] LEVEN: A Large-Scale Chinese Legal Event Detection Dataset
[2203.08556] LEVEN: A Large-Scale Chinese Legal Event Detection Dataset
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Computer Science > Computation and Language
arXiv:2203.08556 (cs)
[Submitted on 16 Mar 2022]
Title:LEVEN: A Large-Scale Chinese Legal Event Detection Dataset
Authors:Feng Yao, Chaojun Xiao, Xiaozhi Wang, Zhiyuan Liu, Lei Hou, Cunchao Tu, Juanzi Li, Yun Liu, Weixing Shen, Maosong Sun Download a PDF of the paper titled LEVEN: A Large-Scale Chinese Legal Event Detection Dataset, by Feng Yao and 9 other authors
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Abstract:Recognizing facts is the most fundamental step in making judgments, hence detecting events in the legal documents is important to legal case analysis tasks. However, existing Legal Event Detection (LED) datasets only concern incomprehensive event types and have limited annotated data, which restricts the development of LED methods and their downstream applications. To alleviate these issues, we present LEVEN a large-scale Chinese LEgal eVENt detection dataset, with 8,116 legal documents and 150,977 human-annotated event mentions in 108 event types. Not only charge-related events, LEVEN also covers general events, which are critical for legal case understanding but neglected in existing LED datasets. To our knowledge, LEVEN is the largest LED dataset and has dozens of times the data scale of others, which shall significantly promote the training and evaluation of LED methods. The results of extensive experiments indicate that LED is challenging and needs further effort. Moreover, we simply utilize legal events as side information to promote downstream applications. The method achieves improvements of average 2.2 points precision in low-resource judgment prediction, and 1.5 points mean average precision in unsupervised case retrieval, which suggests the fundamentality of LED. The source code and dataset can be obtained from this https URL.
Comments:
Accepted to ACL2022 Findings
Subjects:
Computation and Language (cs.CL); Artificial Intelligence (cs.AI)
Cite as:
arXiv:2203.08556 [cs.CL]
(or
arXiv:2203.08556v1 [cs.CL] for this version)
https://doi.org/10.48550/arXiv.2203.08556
Focus to learn more
arXiv-issued DOI via DataCite
Submission history From: Feng Yao [view email] [v1]
Wed, 16 Mar 2022 11:40:02 UTC (1,332 KB)
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LEVEN Dataset | Papers With Code
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## Overview
LEVEN is the **largest Legal Event Detection** dataset as well as the **largest Chinese Event Detection** dataset.
### Large Scale
LEVEN contains 8,116 legal documents, 63,616 sentences, and 150,977 event mentions.
### High Coverage
LEVEN contains 108 event types in total, including 64 charge-oriented events and 44 general events.
## Miscs
LEVEN is adopted for the [Event Detection Track of CAIL 2022](http://cail.cipsc.org.cn/task1.html?raceID=1&cail_tag=2022).
Check out the LEVEN [repo](https://github.com/thunlp/LEVEN/) for more details.
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--------- LEVEN: A Large-Scale Chinese Legal Event Detection Dataset
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LEVEN (Legal Event Detection Dataset)
Introduced by Yao et al. in LEVEN: A Large-Scale Chinese Legal Event Detection Dataset
Overview
LEVEN is the largest Legal Event Detection dataset as well as the largest Chinese Event Detection dataset.
Large Scale
LEVEN contains 8,116 legal documents, 63,616 sentences, and 150,977 event mentions.
High Coverage
LEVEN contains 108 event types in total, including 64 charge-oriented events and 44 general events.
Miscs
LEVEN is adopted for the Event Detection Track of CAIL 2022.
Check out the LEVEN repo for more details.
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Re15:读论文 LEVEN: A Large-Scale Chinese Legal Event Detection Dataset_leven数据集-CSDN博客
>Re15:读论文 LEVEN: A Large-Scale Chinese Legal Event Detection Dataset_leven数据集-CSDN博客
Re15:读论文 LEVEN: A Large-Scale Chinese Legal Event Detection Dataset
最新推荐文章于 2024-02-01 17:37:27 发布
诸神缄默不语
最新推荐文章于 2024-02-01 17:37:27 发布
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论文名称:LEVEN: A Large-Scale Chinese Legal Event Detection Dataset
本文是2022年ACL论文,作者来自清华。提出了一个法律事件抽取数据集。 本文提出了一个考虑综合事件类型、数据量目前最大的法律文本事实抽取数据集,包括了与案件相关的事件和普通事件。实验证明使用法律事件作为side information能够增强下游法律裁决预测任务的准确性。 这篇和EPM1都是2022年ACL,真是牛逼……我都搞不懂EPM那种玄幻叠叠乐是怎么能发顶会的,一点都没有简洁之美……而且EPM的数据量也比LEVEN小很多。
本文仅简略概括,细节待补。
文章目录
1. Background2. 数据集LEVEN3. baseline和实验结果3.1 事件抽取3.2 下游任务
1. Background
事件抽取:抽取event triggers,并将其分类到event types
2. 数据集LEVEN
包含了charge-related events和general events
3. baseline和实验结果
3.1 事件抽取
token classification: BiLSTM, BERTDynamic max-pooling: DMCNN, DMBERTSequence labeling: BiLSTM+CRF, BERT+CRF
3.2 下游任务
实验结果:直接将事件信息在下游任务上用作side information,在low-resource judgment prediction任务和unsupervised case retrieval任务上有提升
Re11:读论文 EPM Legal Judgment Prediction via Event Extraction with Constraints ↩︎
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Re15:读论文 LEVEN: A Large-Scale Chinese Legal Event Detection Dataset
论文阅读笔记:LEVEN: A Large-Scale Chinese Legal Event Detection Dataset
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Legal Case Reports DataSet 法律案件数据集-数据集
03-19
Legal Case Reports 是澳大利亚联邦法院的案件数据集,主要用于文本摘要。该数据集包含 2006 年至 2009 年的所有案例,来源为 AustL II,发布者将其用于构建实验摘要和引文分析,每个文件中均包含流星语、引文句子、引文标语和引文类别。
Legal Case Reports DataSet 法律案件数据集_datasets.txt
Legal Case Reports DataSet 法律案件数据集_corpus_datasets.zip
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