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Neural Legal Judgment Prediction in English
Open accessAbstract
Legal judgment prediction is the task of automatically predicting the outcome of a court case, given a text describing the case's facts.Previous work on using neural models for this task has focused on Chinese; only featurebased models (e.g., using bags of words and topics) have been considered in English.We release a new English legal judgment prediction dataset, containing cases from the European Court of Human Rights.We evaluate a broad variety of neural models on the new dataset, establishing strong baselines that surpass previous feature-based models in three tasks: (1) binary violation classification; (2) multi-label classification; (3) case importance prediction.We also explore if models are biased towards demographic information via data anonymization.As a side-product, we propose a hierarchical version of BERT, which bypasses BERT's length limitation.
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Metadata
- Authors
- Chalkidis, I., Androutsopoulos, I., & Aletras, N.
- Affiliations
- Athens University of Economics and Business (GR)
- Venue
- Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics
- Published
- 2019
- Pages
- 4317-4323
- ISSN
- 0736-587X (ISSN-L)
- OpenAlex
- W2948586190
- Cited by
- 352
- References
- 26
- Citations by year
- 2026: 53 · 2025: 62 · 2024: 53 · 2023: 69 · 2022: 46 · 2021: 46 · 2020: 22 · 2019: 1
- FWCI
- 198.12
- Type
- conference paper
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- cc-by
- Locations
- Proceedings of the conference - Association for Computational Linguistics. Meeting (publishedVersion, cc-by)
- White Rose Research Online (University of Leeds, The University of Sheffield, University of York) (acceptedVersion)
- arXiv (Cornell University) (submittedVersion)
- arXiv (Cornell University)
- Funders
- Athens University of Economics and Business
- Topics
- Social Sciences › Law › Artificial Intelligence in Law
- Physical Sciences › Computer Science › Artificial Intelligence › Topic Modeling
- Physical Sciences › Computer Science › Artificial Intelligence › Machine Learning in Healthcare
- Keywords
- legal judgment prediction, European Court of Human Rights, English legal texts, multi-label classification, demographic bias, data anonymization, neural language models
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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