---
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. Each interaction is manually written to reflect realistic single-turn and multi-turn conversational scenarios. The reference documents are drawn from general-use reference texts and documents.

## Source

| Subset | Source |
|:--|:--|
| QA | Expert-crafted single-turn and multi-turn conversations based on general-use documents |
| Documents | General reference texts and documents |

## 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. |