| --- |
| 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. | |
