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--- |
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configs: |
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- config_name: crag_task_1_and_2_subset_1 |
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data_files: subset/crag_task_1_and_2/crag_task_1_and_2_dev_v4_subset_1.jsonl.bz2 |
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- config_name: crag_task_1_and_2_subset_2 |
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data_files: subset/crag_task_1_and_2/crag_task_1_and_2_dev_v4_subset_2.jsonl.bz2 |
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- config_name: crag_task_1_and_2_subset_3 |
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data_files: subset/crag_task_1_and_2/crag_task_1_and_2_dev_v4_subset_3.jsonl.bz2 |
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- config_name: crag_task_1_and_2_subset_4 |
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data_files: subset/crag_task_1_and_2/crag_task_1_and_2_dev_v4_subset_4.jsonl.bz2 |
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- config_name: crag_task_1_and_2_subset_5 |
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data_files: subset/crag_task_1_and_2/crag_task_1_and_2_dev_v4_subset_5.jsonl.bz2 |
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- config_name: crag_task_1_and_2_subset_6 |
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data_files: subset/crag_task_1_and_2/crag_task_1_and_2_dev_v4_subset_6.jsonl.bz2 |
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- config_name: crag_task_1_and_2_subset_7 |
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data_files: subset/crag_task_1_and_2/crag_task_1_and_2_dev_v4_subset_7.jsonl.bz2 |
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- config_name: crag_task_1_and_2_subset_8 |
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data_files: subset/crag_task_1_and_2/crag_task_1_and_2_dev_v4_subset_8.jsonl.bz2 |
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- config_name: crag_task_1_and_2_subset_9 |
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data_files: subset/crag_task_1_and_2/crag_task_1_and_2_dev_v4_subset_9.jsonl.bz2 |
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- config_name: crag_task_1_and_2_subset_10 |
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data_files: subset/crag_task_1_and_2/crag_task_1_and_2_dev_v4_subset_10.jsonl.bz2 |
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- config_name: crag_task_1_and_2_subset_11 |
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data_files: subset/crag_task_1_and_2/crag_task_1_and_2_dev_v4_subset_11.jsonl.bz2 |
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- config_name: crag_task_1_and_2_subset_12 |
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data_files: subset/crag_task_1_and_2/crag_task_1_and_2_dev_v4_subset_12.jsonl.bz2 |
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- config_name: crag_task_1_and_2_subset_13 |
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data_files: subset/crag_task_1_and_2/crag_task_1_and_2_dev_v4_subset_13.jsonl.bz2 |
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- config_name: crag_task_1_and_2_subset_14 |
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data_files: subset/crag_task_1_and_2/crag_task_1_and_2_dev_v4_subset_14.jsonl.bz2 |
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- config_name: crag_task_1_and_2_subset_15 |
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data_files: subset/crag_task_1_and_2/crag_task_1_and_2_dev_v4_subset_15.jsonl.bz2 |
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- config_name: crag_task_1_and_2_subset_16 |
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data_files: subset/crag_task_1_and_2/crag_task_1_and_2_dev_v4_subset_16.jsonl.bz2 |
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- config_name: crag_task_1_and_2_subset_17 |
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data_files: subset/crag_task_1_and_2/crag_task_1_and_2_dev_v4_subset_17.jsonl.bz2 |
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- config_name: crag_task_1_and_2_subset_18 |
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data_files: subset/crag_task_1_and_2/crag_task_1_and_2_dev_v4_subset_18.jsonl.bz2 |
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- config_name: crag_task_1_and_2_subset_19 |
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data_files: subset/crag_task_1_and_2/crag_task_1_and_2_dev_v4_subset_19.jsonl.bz2 |
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- config_name: crag_task_1_and_2_subset_20 |
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data_files: subset/crag_task_1_and_2/crag_task_1_and_2_dev_v4_subset_20.jsonl.bz2 |
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license: cc-by-nc-4.0 |
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task_categories: |
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- question-answering |
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- summarization |
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language: |
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- en |
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tags: |
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- music |
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- finance |
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size_categories: |
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- 1K<n<10K |
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pretty_name: CRA |
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--- |
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|
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Datasets are taken from Facebook's [CRAG: Comprehensive RAG Benchmark](https://github.com/facebookresearch/CRAG), see their [arXiv paper](https://arxiv.org/abs/2406.04744) for details about the dataset construction. |
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# CRAG Sampler |
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We have added a simple Python tool for performing stratified sampling on CRAG data. |
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## Installation |
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### Local Development Install (Recommended) |
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```bash |
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git clone https://huggingface.co/Quivr/CRAG.git |
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cd CRAG |
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pip install -r requirements.txt # Install dependencies |
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pip install -e . # Install package in development mode |
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``` |
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## Quick Start |
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### Running the example |
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```bash |
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python -m examples.basic_sampling |
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``` |
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# CRAG dataset |
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CRAG (Comprehensive RAG Benchmark) is a rich and comprehensive factual question answering benchmark designed to advance research in RAG. The public version of the dataset includes: |
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- 2706 Question-Answer pairs |
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- 5 domains: Finance, Sports, Music, Movie, and Open domain |
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- 8 types of questions (see image below): simple, simple with condition, set, comparison, aggregation, multi-hop, post-processing heavy, and false premise |
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The datasets `crag_task_1_and_2_dev_v4_subsample_*.json.bz2` have been created from the dataset [crag_task_1_and_2_dev_v4.jsonl.bz2](https://github.com/facebookresearch/CRAG/raw/refs/heads/main/data/crag_task_1_and_2_dev_v4.jsonl.bz2?download=) available on CRAG's GitHub repository. |
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For an easier handling and download of the dataset, we have used our CRAG sampler to split the 2706 rows of the original file in 5 subsamples, following the procedure below: |
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1. We have created a new label `answer_type`, classifying the answers in 3 categories: |
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- `invalid` for any answer == "invalid question" |
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- `no_answer` for any answer == "i don't know" |
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- `valid` for any other answer |
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2. We have considered the labels `answer_type`, `domain`, `question_type` and `static_or_dynamic` and performed stratified sampling, splitting the datasets in 5 subsamples. Each subsample has thus the same statistical properties of the full dataset. |
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We report below the data schema as provided in [CRAG's GitHub repository](https://github.com/facebookresearch/CRAG/blob/main/docs/dataset.md). |
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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. | |
