ECHR: Legal Corpus for Argument Mining
In this paper, we publicly release an annotated corpus of 42 decisions of the European Court of Human Rights (ECHR). The corpus is annotated in terms of three types of clauses useful in argument mining: premise, conclusion, and non-argument parts of the text. Furthermore, relationships among the premises and conclusions are mapped. We present baselines for three tasks that lead from unstructured texts to structured arguments. The tasks are argument clause recognition, clause relation prediction, and premise/conclusion recognition. Despite a straightforward application of the bidirectional encoders from Transformers (BERT), we obtained very promising results F1 0.765 on argument recognition, 0.511 on relation prediction, and 0.859/0.628 on premise/conclusion recognition). The results suggest the usefulness of pre-trained language models based on deep neural network architectures in argument mining. Because of the simplicity of the baselines, there is ample space for improvement in future work based on the released corpus.
Code (0)
등록된 구현이 없습니다.
Tasks
Argument MiningRelationRelation PredictionSimilar Papers 제목 키워드 기반
Mining Legal Arguments in Court Decisions
Identifying, classifying, and analyzing arguments in legal discourse has been a prominent area of research since the inception of the argument mining field. However, there has been a major discrepancy between the way nat…
Argument MiningLAR-ECHR: A New Legal Argument Reasoning Task and Dataset for Cases of the European Court of Human Rights
We present Legal Argument Reasoning (LAR), a novel task designed to evaluate the legal reasoning capabilities of Large Language Models (LLMs). The task requires selecting the correct next statement (from multiple choice …
Legal ReasoningMultiple-choiceEnhancing Legal Argument Mining with Domain Pre-training and Neural Networks
The contextual word embedding model, BERT, has proved its ability on downstream tasks with limited quantities of annotated data. BERT and its variants help to reduce the burden of complex annotation work in many interdis…
Argument MiningLaCour!: Enabling Research on Argumentation in Hearings of the European Court of Human Rights
Why does an argument end up in the final court decision? Was it deliberated or questioned during the oral hearings? Was there something in the hearings that triggered a particular judge to write a dissenting opinion? Des…
SentenceLAMUS: A Large-Scale Corpus for Legal Argument Mining from U.S. Caselaw using LLMs
Legal argument mining aims to identify and classify the functional components of judicial reasoning, such as facts, issues, rules, analysis, and conclusions. Progress in this area is limited by the lack of large-scale, h…
Sentence ClassificationArgument Mining