TransLaw: A Large-Scale Dataset and Multi-Agent Benchmark Simulating Professional Translation of Hong Kong Case Law
arXiv:2507.00875v3 Announce Type: replace Abstract: Translating Hong Kong Court Judgments from English to Traditional Chinese is mandated by Articles 8-9 of the Basic Law, yet remains constrained by a shortage of parallel resources and rigorous demands on legal terminology, citation format, and judicial style. We introduce HKCFA Judgment 97-22, the first large-scale sentence-aligned parallel corpus for HK case law, comprising 344 professionally translated judgments (11,099 sentence pairs; 2.1M tokens) spanning 1997-2022. Building on this resource, we propose TransLaw, a multi-agent framework t
The increasing sophistication of large language models and the demand for specialized AI applications are driving the creation of domain-specific datasets and multi-agent frameworks.
This development indicates a progression towards highly specialized AI agents capable of performing complex, regulated professional tasks, particularly in fields with high linguistic and contextual rigor.
The availability of a large-scale, professionally translated legal corpus enables the development of AI agents that can handle nuanced legal translation and interpretation, potentially transforming legal services.
- · Hong Kong legal sector
- · AI agents developers
- · Legaltech industry
- · Computational linguistics researchers
- · Traditional human legal translators
- · Generic translation software
- · Legal outsourcing firms relying on manual processes
Improved efficiency and accuracy in legal translation within Hong Kong's bilingual legal system.
The precedent set could lead to similar datasets and multi-agent systems for other specialized, high-stakes multilingual domains globally.
Enhanced AI capabilities in legal interpretation could eventually influence legal precedent and judicial processes beyond mere translation.
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