⚖️ A Statutory Article Retrieval Dataset in French.

Last update: Nov 17, 2022

Overview

A Statutory Article Retrieval Dataset in French

This repository contains the Belgian Statutory Article Retrieval Dataset (BSARD), as well as the code to reproduce the experimental results from the associated paper by A. Louis, G. Spanakis, and G. Van Dijck.

Abstract. Statutory article retrieval is the task of automatically retrieving law articles relevant to a legal question. While recent advances in natural language processing have sparked considerable interest in many legal tasks, statutory article retrieval remains primarily untouched due to the scarcity of large-scale and high-quality annotated datasets. To address this bottleneck, we introduce the Belgian Statutory Article Retrieval Dataset (BSARD), which consists of 1,100+ French native legal questions labeled by experienced jurists with relevant articles from a corpus of 22,600+ Belgian law articles. Using BSARD, we benchmark several unsupervised information retrieval methods based on term weighting and pooled embeddings. Our best performing baseline achieves 50.8% [email protected], which is promising for the feasibility of the task and indicates that there is still substantial room for improvement. By the specificity of the data domain and addressed task, BSARD presents a unique challenge problem for future research on legal information retrieval.

Documentation

Detailed documentation on the dataset and how to reproduce the main experimental results can be found here.

Citation

For attribution in academic contexts, please cite this work as:

@article{louis2021statutory,
  title = {A Statutory Article Retrieval Dataset in French},
  author = {Louis, Antoine and Spanakis, Gerasimos and Van Dijck, Gijs},
  journal = {arXiv preprint arXiv:2108.11792},
  year = {2021},
}

License

This repository is licensed under the terms of the CC BY-NC-SA 4.0 license.

You might also like...

🏆 The 1st Place Submission to AICity Challenge 2021 Natural Language-Based Vehicle Retrieval Track (Alibaba-UTS submission)

26 Apr 29, 2021

Code for papers "Generation-Augmented Retrieval for Open-Domain Question Answering" and "Reader-Guided Passage Reranking for Open-Domain Question Answering", ACL 2021

This repo provides the code of the following papers: (GAR) "Generation-Augmented Retrieval for Open-domain Question Answering", ACL 2021 (RIDER) "Read

49 Dec 26, 2022

Composed Image Retrieval using Pretrained LANguage Transformers (CIRPLANT)

CIRPLANT This repository contains the code and pre-trained models for Composed Image Retrieval using Pretrained LANguage Transformers (CIRPLANT) For d

29 Nov 17, 2022

[ICCV 2021] Instance-level Image Retrieval using Reranking Transformers

Instance-level Image Retrieval using Reranking Transformers Fuwen Tan, Jiangbo Yuan, Vicente Ordonez, ICCV 2021. Abstract Instance-level image retriev

86 Dec 28, 2022

Unsupervised Document Expansion for Information Retrieval with Stochastic Text Generation

Unsupervised Document Expansion for Information Retrieval with Stochastic Text Generation Official Code Repository for the paper "Unsupervised Documen

2 Oct 26, 2021

Question and answer retrieval in Turkish with BERT

trfaq Google supported this work by providing Google Cloud credit. Thank you Google for supporting the open source! 🎉 What is this? At this repo, I'm

13 Oct 10, 2022

Legal text retrieval for python

legal-text-retrieval Overview This system contains 2 steps: generate training data containing negative sample found by mixture score of cosine(tfidf)

22 Dec 6, 2022

Implementation of Memorizing Transformers (ICLR 2022), attention net augmented with indexing and retrieval of memories using approximate nearest neighbors, in Pytorch

Memorizing Transformers - Pytorch Implementation of Memorizing Transformers (ICLR 2022), attention net augmented with indexing and retrieval of memori

364 Jan 6, 2023

Easily train your own text-generating neural network of any size and complexity on any text dataset with a few lines of code.

textgenrnn Easily train your own text-generating neural network of any size and complexity on any text dataset with a few lines of code, or quickly tr

4.8k Dec 30, 2022

Comments

transformers library version should be specified

Hi,

As specified in the documentation, I made the environment from the yml file: time conda env create -n bsard -f environment.yml

However, I run into an error when doing the grid search:

Traceback (most recent call last):                                                                                                                                                   
  File "scripts/search_hyperparameters.py", line 11, in <module>
    from retriever import Word2vecRetriever, FasttextRetriever, BERTRetriever
  File "/u/salaunol/Documents/_2021_automne/bsard/scripts/retriever.py", line 16, in <module>
    from transformers import (CamembertModel, CamembertTokenizer,
ImportError: cannot import name 'CamembertModel' from 'transformers' (/u/salaunol/anaconda3/envs/bsard/lib/python3.8/site-packages/transformers/__init__.py)

The transformers version was the following: transformers 2.1.1 pyhd3eb1b0_0

I fixed it with pip install transformers==2.5.0 but it would be preferable to specify the version for each library in environment.yml

Edit: issue submitted too fast

opened by oliviersalaun 1

Releases(v1.0)

v1.0(Aug 26, 2021)

The Belgian Statutory Article Retrieval Dataset (BSARD) v1.0 is a French native corpus for studying statutory article retrieval. BSARD consists of more than 22,600 statutory articles from Belgian law and about 1,100 legal questions posed by Belgian citizens and labeled by experienced jurists with relevant articles from the corpus.
Source code(tar.gz)
Source code(zip)

Owner

Maastricht Law & Tech Lab

The Lab aims to offer innovative education and to build a creative community of researchers at the intersections of law, technology and data science.

GitHub Repository

State of the Art Natural Language Processing

Spark NLP: State of the Art Natural Language Processing Spark NLP is a Natural Language Processing library built on top of Apache Spark ML. It provide

3k Jan 05, 2023

A PyTorch implementation of VIOLET

VIOLET: End-to-End Video-Language Transformers with Masked Visual-token Modeling A PyTorch implementation of VIOLET Overview VIOLET is an implementati

119 Dec 30, 2022

Google's Meena transformer chatbot implementation

Here's my attempt at recreating Meena, a state of the art chatbot developed by Google Research and described in the paper Towards a Human-like Open-Domain Chatbot.

94 Dec 25, 2022

BERTAC (BERT-style transformer-based language model with Adversarially pretrained Convolutional neural network)

BERTAC (BERT-style transformer-based language model with Adversarially pretrained Convolutional neural network) BERTAC is a framework that combines a

6 Jan 24, 2022

A natural language modeling framework based on PyTorch

Overview PyText is a deep-learning based NLP modeling framework built on PyTorch. PyText addresses the often-conflicting requirements of enabling rapi

6.4k Dec 27, 2022

BeautyNet is an AI powered model which can tell you whether you're beautiful or not.

BeautyNet BeautyNet is an AI powered model which can tell you whether you're beautiful or not. Download Dataset from here:https://www.kaggle.com/gpios

0 May 06, 2022

Transformer-based Text Auto-encoder (T-TA) using TensorFlow 2.

T-TA (Transformer-based Text Auto-encoder) This repository contains codes for Transformer-based Text Auto-encoder (T-TA, paper: Fast and Accurate Deep

13 Dec 13, 2022

✨Rubrix is a production-ready Python framework for exploring, annotating, and managing data in NLP projects.

✨A Python framework to explore, label, and monitor data for NLP projects

1.5k Jan 02, 2023

Linking data between GBIF, Biodiverse, and Open Tree of Life

GBIF-biodiverse-OpenTree Linking data between GBIF, Biodiverse, and Open Tree of Life The python scripts will rely on opentree and Dendropy. To set up

2 Oct 03, 2022

Practical Machine Learning with Python

Master the essential skills needed to recognize and solve complex real-world problems with Machine Learning and Deep Learning by leveraging the highly popular Python Machine Learning Eco-system.

2k Jan 08, 2023

Code for PED: DETR For (Crowd) Pedestrian Detection

36 Sep 13, 2022

PhoNLP: A BERT-based multi-task learning toolkit for part-of-speech tagging, named entity recognition and dependency parsing

PhoNLP is a multi-task learning model for joint part-of-speech (POS) tagging, named entity recognition (NER) and dependency parsing. Experiments on Vietnamese benchmark datasets show that PhoNLP prod

109 Dec 02, 2022

Translation for Trilium Notes. Trilium Notes 中文版.

Trilium Translation 中文说明 This repo provides a translation for the awesome Trilium Notes. Currently, I have translated Trilium Notes into Chinese. Test

743 Jan 08, 2023

Application for shadowing Chinese.

chinese-shadowing Simple APP for shadowing chinese. With this application, it is very easy to record yourself, play the sound recorded and listen to s

5 Sep 06, 2022

Universal End2End Training Platform, including pre-training, classification tasks, machine translation, and etc.

背景安装教程快速上手（一）预训练模型（二）机器翻译（三）文本分类 TenTrans 进阶 1. 多语言机器翻译 2. 跨语言预训练背景 TrenTrans是一个统一的端到端的多语言多任务预训练平台，支持多种预训练方式，以及序列生成和自然语言理解任务。安装教程 git clone git

42 Dec 20, 2022

:mag: Transformers at scale for question answering & neural search. Using NLP via a modular Retriever-Reader-Pipeline. Supporting DPR, Elasticsearch, HuggingFace's Modelhub...

Haystack is an end-to-end framework that enables you to build powerful and production-ready pipelines for different search use cases. Whether you want

6.4k Jan 09, 2023