DISC-Law-SFT: Chinese Legal Text for Supervised Fine-Tuning

DISC-Law-SFT is a supervised fine-tuning dataset for Chinese legal intelligent systems. It was created by ShengbinYue and covers multiple legal scenarios, including information extraction and question answering. The dataset was last updated on Hugging Face in May 2025.

Use Cases

• Fine-tuning models for legal information extraction based on described legal scenarios.
• Training models for legal judgment prediction based on described legal scenarios.
• Developing systems for legal document summarization based on described legal scenarios.
• Building legal question-answering assistants based on described legal scenarios.

Strengths

• Dataset is described as high-quality and designed for supervised fine-tuning.
• Covers multiple legal scenarios, including extraction, prediction, summarization, and QA.
• Comprises two subsets, DISC-Law-SFT-Pair and another, suggesting structured training data.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count, file formats, and exact size are unknown, which may limit suitability assessment.

Provenance

Source

ShengbinYue on Hugging Face.

Collection Method

Constructed for training legal intelligent systems; method details are not specified.

Time Range

null

Freshness

Last updated 2025-05-22 08:47:55; freshness should be verified.

Geography

Focus is on Chinese legal text; specific geographic coverage is not detailed.