README.md

metadata

configs:
  - config_name: QA
    data_files: QA.json
    features:
      - name: conversation_id
        dtype: string
      - name: turn_id
        dtype: int32
      - name: question
        dtype: string
      - name: ground_truth
        dtype: string
  - config_name: Documents
    data_files: Documents.json
    features:
      - name: id
        dtype: string
      - name: content
        dtype: string

Dataset Structure

This dataset contains two subsets:

• QA: Question-answer pairs, spanning both single-turn and multi-turn interactions

  • conversation_id (string): A unique identifier for a conversation session. In multi-turn configurations, multiple rows share the same ID to represent a continuous dialogue.
  • turn_id (int32): The sequential order of messages within a session (0 represents the first user query).
  • question (string): The question text.
  • ground_truth (string): The reference response.

• Documents: Document contents referenced by the QA subset

  • id (string): Unique document identifier.
  • content (string): The document text content.

Data Construction

The data is constructed using Expert-Crafted Data; Questions and their corresponding reference answers are crafted by domain experts in the legal and judicial field. Each interaction is manually written to reflect realistic single-turn and multi-turn conversational scenarios. The reference documents are drawn from legal reference texts and statutory laws.

Source

Subset	Source
QA	Expert-crafted single-turn and multi-turn conversations based on legal statutes and regulations
Documents	Legal statutes, regulations, and reference texts

Review Process

All data undergoes a manual human review process. Problematic samples are directly removed or modified while preserving their original intent. Reviewers may also use automated tools to assist in this process.

#	Criterion	Description
1	Factual Accuracy	The ground truth response must be legally accurate.
2	Conversational Coherence	In multi-turn settings, each turn must flow naturally from the preceding context without contradiction or redundancy.
3	Completeness and Clarity	Each question and answer must be self-contained within its conversation context and free of ambiguity.