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README.md

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+---
+license: mit
+task_categories:
+- text-retrieval
+language:
+- de
+- zh
+tags:
+- legal
+- retrieval
+- embedding
+size_categories:
+- 10K<n<100K
+---
+
+# legal-retrieval-pairs-v2
+
+Multilingual legal **retrieval training pairs** used to train `Hanno-Labs/dinghy-law-4b` (Qwen3-Embedding-4B base).
+Additive coverage beyond [`legal-retrieval-pairs-v1`](https://huggingface.co/datasets/Hanno-Labs/legal-retrieval-pairs-v1)
+(the 0.6B pairs). Each row: `{query, positive, source}`, nDCG-style query→relevant-passage.
+
+## Sources (both MIT-licensed, leak-guarded against the MTEB(Law) eval corpora)
+
+- **`de_legal`** (80k) — German court decisions from [SH108/german-court-decisions](https://huggingface.co/datasets/SH108/german-court-decisions)
+  (MIT; underlying decisions public-domain, §5 UrhG). Query→decision-passage pairs generated by a same-language grounded
+  query-gen rig (Gemma-4-QAT), grounding-verified. Targets the German LegalQuAD/GerDaLIR gap.
+- **`zh_case`** (12.7k) — Chinese **case→case** precedent pairs from [china-ai-law-challenge/cail2018](https://huggingface.co/datasets/china-ai-law-challenge/cail2018)
+  (MIT). Within each criminal charge, each case is paired with its most fact-similar same-charge case (model2vec
+  nearest-neighbor). This is *case→relevant-precedent* shape (not QA), built for LeCaRDv2-style case retrieval. NOT
+  LeCaRDv2's corpus.
+
+## License
+
+MIT. Both upstream sources are MIT. Attribution to CAIL2018 and SH108/german-court-decisions appreciated.