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AUEB-NLP/lar-echr
The declared licence (cc-by-nc-sa-4.0) is classified as having use restrictions.
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Citation text from the card
@inproceedings{chlapanis-etal-2024-lar,
title = "{LAR}-{ECHR}: A New Legal Argument Reasoning Task and Dataset for Cases of the {E}uropean Court of Human Rights",
author = "Chlapanis, Odysseas S. and
Galanis, Dimitrios and
Androutsopoulos, Ion",
editor = "Aletras, Nikolaos and
Chalkidis, Ilias and
Barrett, Leslie and
Goanț{\u{a}}, C{\u{a}}t{\u{a}}lina and
Preoțiuc-Pietro, Daniel and
Spanakis, Gerasimos",
booktitle = "Proceedings of the Natural Legal Language Processing Workshop 2024",
month = nov,
year = "2024",
address = "Miami, FL, USA",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2024.nllp-1.22/",
doi = "10.18653/v1/2024.nllp-1.22",
pages = "267--279",
abstract = "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 options) in a chain of legal arguments from court proceedings, given the facts of the case. We constructed a dataset (LAR-ECHR) for this task using cases from the European Court of Human Rights (ECHR). We evaluated seven general-purpose LLMs on LAR-ECHR and found that (a) the ranking of the models is aligned with that of LegalBench, an established US-based legal reasoning benchmark, even though LAR-ECHR is based on EU law, (b) LAR-ECHR distinguishes top mode
The same facts for your agent
A free MCP server at mcp.datalicense.uk/mcp. Connect it from an MCP client such as Claude or Cursor.
dataset_licence({ "id": "AUEB-NLP/lar-echr" })
signal: "restrictive"
stated_licence: "cc-by-nc-sa-4.0"
sources: 0