LAUKIN: New Multi-jurisdictional Legal Contract Dataset for Cross-border Equivalence Classification
Researchers have introduced LAUKIN, a dataset of 14,727 clause pairs from contracts across Australia, the UK, and India, labeled for legal equivalence to support cross-jurisdictional contract analysis. The dataset addresses a gap in legal NLP research, as existing datasets typically focus on single jurisdictions despite multinational companies' need for cross-border contract review. The work establishes a challenging benchmark with a best model performance of 65.11% macro-F1, revealing that drafting conventions diverge significantly across jurisdictions despite shared legal heritage.
Researchers have created LAUKIN (Legal equivalence dataset of Australia, UK, and INdia), a new benchmark dataset designed to support natural language processing research in cross-jurisdictional contract analysis. The dataset contains 14,727 clause pairs from 204 contracts spanning 8 agreement types, with 3,000 manually annotated by legal experts as either Equivalent or Not Equivalent across three language pairs (AU-UK, UK-IN, IN-AU). The team developed a multi-stage retrieval and reranking pipeline to construct initial clause pair mappings before expert annotation. Evaluation of 12 models across 4 techniques achieved a best macro-F1 score of 65.11%, establishing LAUKIN as a challenging benchmark. The results demonstrate that despite shared common law heritage, drafting conventions diverge substantially across jurisdictions, making automated equivalence classification non-trivial. The dataset also includes 11,727 unlabeled training pairs to support future semi-supervised learning research.
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- arXiv cs.CLCenter
LAUKIN: A Multi-jurisdictional Common Law Contract Dataset
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