---
_id: '48290'
abstract:
- lang: eng
  text: <jats:title>Abstract</jats:title><jats:p>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 natural language processing (NLP) researchers model and annotate arguments
    in court decisions and the way legal experts understand and analyze legal argumentation.
    While computational approaches typically simplify arguments into generic premises
    and claims, arguments in legal research usually exhibit a rich typology that is
    important for gaining insights into the particular case and applications of law
    in general. We address this problem and make several substantial contributions
    to move the field forward. First, we design a new annotation scheme for legal
    arguments in proceedings of the European Court of Human Rights (ECHR) that is
    deeply rooted in the theory and practice of legal argumentation research. Second,
    we compile and annotate a large corpus of 373 court decisions (2.3M tokens and
    15k annotated argument spans). Finally, we train an argument mining model that
    outperforms state-of-the-art models in the legal NLP domain and provide a thorough
    expert-based evaluation. All datasets and source codes are available under open
    lincenses at <jats:ext-link xmlns:xlink="http://www.w3.org/1999/xlink" ext-link-type="uri"
    xlink:href="https://github.com/trusthlt/mining-legal-arguments">https://github.com/trusthlt/mining-legal-arguments</jats:ext-link>.</jats:p>
author:
- first_name: Ivan
  full_name: Habernal, Ivan
  id: '101881'
  last_name: Habernal
- first_name: Daniel
  full_name: Faber, Daniel
  last_name: Faber
- first_name: Nicola
  full_name: Recchia, Nicola
  last_name: Recchia
- first_name: Sebastian
  full_name: Bretthauer, Sebastian
  last_name: Bretthauer
- first_name: Iryna
  full_name: Gurevych, Iryna
  last_name: Gurevych
- first_name: Indra
  full_name: Spiecker genannt Döhmann, Indra
  last_name: Spiecker genannt Döhmann
- first_name: Christoph
  full_name: Burchard, Christoph
  last_name: Burchard
citation:
  ama: Habernal I, Faber D, Recchia N, et al. Mining legal arguments in court decisions.
    <i>Artificial Intelligence and Law</i>. Published online 2023. doi:<a href="https://doi.org/10.1007/s10506-023-09361-y">10.1007/s10506-023-09361-y</a>
  apa: Habernal, I., Faber, D., Recchia, N., Bretthauer, S., Gurevych, I., Spiecker
    genannt Döhmann, I., &#38; Burchard, C. (2023). Mining legal arguments in court
    decisions. <i>Artificial Intelligence and Law</i>. <a href="https://doi.org/10.1007/s10506-023-09361-y">https://doi.org/10.1007/s10506-023-09361-y</a>
  bibtex: '@article{Habernal_Faber_Recchia_Bretthauer_Gurevych_Spiecker genannt Döhmann_Burchard_2023,
    title={Mining legal arguments in court decisions}, DOI={<a href="https://doi.org/10.1007/s10506-023-09361-y">10.1007/s10506-023-09361-y</a>},
    journal={Artificial Intelligence and Law}, publisher={Springer Science and Business
    Media LLC}, author={Habernal, Ivan and Faber, Daniel and Recchia, Nicola and Bretthauer,
    Sebastian and Gurevych, Iryna and Spiecker genannt Döhmann, Indra and Burchard,
    Christoph}, year={2023} }'
  chicago: Habernal, Ivan, Daniel Faber, Nicola Recchia, Sebastian Bretthauer, Iryna
    Gurevych, Indra Spiecker genannt Döhmann, and Christoph Burchard. “Mining Legal
    Arguments in Court Decisions.” <i>Artificial Intelligence and Law</i>, 2023. <a
    href="https://doi.org/10.1007/s10506-023-09361-y">https://doi.org/10.1007/s10506-023-09361-y</a>.
  ieee: 'I. Habernal <i>et al.</i>, “Mining legal arguments in court decisions,” <i>Artificial
    Intelligence and Law</i>, 2023, doi: <a href="https://doi.org/10.1007/s10506-023-09361-y">10.1007/s10506-023-09361-y</a>.'
  mla: Habernal, Ivan, et al. “Mining Legal Arguments in Court Decisions.” <i>Artificial
    Intelligence and Law</i>, Springer Science and Business Media LLC, 2023, doi:<a
    href="https://doi.org/10.1007/s10506-023-09361-y">10.1007/s10506-023-09361-y</a>.
  short: I. Habernal, D. Faber, N. Recchia, S. Bretthauer, I. Gurevych, I. Spiecker
    genannt Döhmann, C. Burchard, Artificial Intelligence and Law (2023).
date_created: 2023-10-19T08:23:39Z
date_updated: 2023-10-19T12:10:02Z
department:
- _id: '34'
- _id: '820'
doi: 10.1007/s10506-023-09361-y
keyword:
- Law
- Artificial Intelligence
language:
- iso: eng
publication: Artificial Intelligence and Law
publication_identifier:
  issn:
  - 0924-8463
  - 1572-8382
publication_status: published
publisher: Springer Science and Business Media LLC
status: public
title: Mining legal arguments in court decisions
type: journal_article
user_id: '15504'
year: '2023'
...