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crag_task_1_dev_v4_release.jsonl.bz2
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version https://git-lfs.github.com/spec/v1
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oid sha256:afa29f2b3facfb5d15aa9cded00d5ec90ff76f3e67279e7b99cfe86659a641ca
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dataset_description-v3.md
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# CRAG Dataset Documentation
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## Dataset Version Information
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- **DATASET_DESCRIPTION_VERSION**: `v3`
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- **DATASET_VERSION**: `v3`
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## Overview
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The CRAG dataset is designed to support the development and evaluation of Retrieval-Augmented Generation (RAG) models. It consists of two main types of data:
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1. **Question Answering Pairs:** Pairs of questions and their corresponding answers.
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2. **Retrieval Contents:** Contents for information retrieval to support answer generation.
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Retrieval contents are divided into two types to simulate practical scenarios for RAG:
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1. **Web Search Results:** For each question, up to `50` **full HTML pages** are stored, retrieved using the question text as a search query. For Task 1, `5 pages` are **randomly selected** from the `top-10 pages`. These pages are likely relevant to the question, but relevance is not guaranteed.
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2. **Mock KGs and APIs:** The Mock API is designed to mimic real-world **Knowledge Graphs (KGs)** or **API searches**. Given some input parameters, they output relevant results, which may or may not be helpful in answering the user's question.
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## Download CRAG Data
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- **Task #1:** [Retreival Summarization Task Page](https://www.aicrowd.com/challenges/meta-comprehensive-rag-benchmark-kdd-cup-2024/problems/retrieval-summarization/dataset_files)
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- **Task #2:** [Mock API Repository](https://gitlab.aicrowd.com/aicrowd/challenges/meta-comprehensive-rag-benchmark-kdd-cup-2024/crag-mock-api)
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- **Task #3:** [End to End Retreival Augmentation Task Page](https://www.aicrowd.com/challenges/meta-comprehensive-rag-benchmark-kdd-cup-2024/problems/end-to-end-retrieval-augmented-generation)
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## Data Schema
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| Field Name | Type | Description |
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|------------------------|---------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------|
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| `interaction_id` | string | A unique identifier for each example. |
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| `query_time` | string | Date and time when the query and the web search occurred. |
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| `domain` | string | Domain label for the query. Possible values: "finance", "music", "movie", "sports", "open". "Open" includes any factual queries not among the previous four domains. |
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| `question_type` | string | Type label about the query. Possible values include: "simple", "simple_w_condition", "comparison", "aggregation", "set", "false_premise", "post-processing", "multi-hop". |
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| `static_or_dynamic` | string | Indicates whether the answer to a question changes and the expected rate of change. Possible values: "static", "slow-changing", "fast-changing", and "real-time". |
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| `query` | string | The question for RAG to answer. |
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| `answer` | string | The gold standard answer to the question. |
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| `alt_ans` | list | Other valid gold standard answers to the question. |
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| `split` | integer | Data split indicator, where 0 is for validation and 1 is for the public test. |
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| `search_results` | list of JSON | Contains up to `k` HTML pages for each query (`k=5` for Task #1 and `k=50` for Task #3), including page name, URL, snippet, full HTML, and last modified time. |
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### Search Results Detail
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| Key | Type | Description |
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|----------------------|--------|---------------------------------------------------------|
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| `page_name` | string | The name of the webpage. |
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| `page_url` | string | The URL of the webpage. |
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| `page_snippet` | string | A short paragraph describing the major content of the page. |
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| `page_result` | string | The full HTML of the webpage. |
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| `page_last_modified` | string | The time when the page was last modified. |
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