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--- |
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dataset_info: |
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features: |
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- name: page_content |
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dtype: string |
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- name: metadata |
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struct: |
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- name: Judge Comments |
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dtype: string |
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- name: Judge Score |
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dtype: string |
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- name: Project Name |
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dtype: string |
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- name: Score |
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dtype: string |
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- name: row |
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dtype: int64 |
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- name: source |
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dtype: string |
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splits: |
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- name: train |
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num_bytes: 16080 |
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num_examples: 50 |
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download_size: 9106 |
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dataset_size: 16080 |
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configs: |
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- config_name: default |
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data_files: |
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- split: train |
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path: data/train-* |
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--- |
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# Dataset Card for ragas-usecase-raw-data |
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## Dataset Description |
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Source data used to generate [ragas-golden-testset-personas](https://huggingface.co/datasets/dwb2023/ragas-golden-testset-personas). Refer to that dataset for additional information. |
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### Dataset Summary |
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Capturing here due to some initial challenges with the source data leading to downstream issues with synthetic data generation. (Garbage In, Garbage Out...) |
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### Dataset Structure |
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The dataset consists of records following the standard LangChain `Document` format: |
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* `page_content` *(string)*: |
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Raw text of the source record. Preserves original whitespace, punctuation, and line breaks. |
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* `metadata` *(struct)*: |
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As-is metadata captured at ingestion (not normalized). |
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* `Judge Comments` *(string)*: Free-text qualitative notes from a judge/evaluator. |
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* `Judge Score` *(string)*: Score exactly as stored in source (e.g., `"4/5"`, `"Good"`, `"N/A"`). |
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* `Project Name` *(string)*: Project/entry name from source. |
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* `Score` *(string)*: Additional score field (distinct from `Judge Score`; may differ). |
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* `row` *(int64)*: Original source row index (stable pointer back to raw data). |
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* `source` *(string)*: Origin identifier (e.g., file name/path/URI). |
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> Notes: Encoding is UTF-8. Scores remain strings by design. Missing/empty fields may occur. |
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### Supported Tasks |
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This dataset is primarily intended for: |
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* **RAGAS test set generation & evaluation** (e.g., faithfulness, answer correctness) |
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* **Loading vector stores for RAG** (retriever benchmarking, recall/precision diagnostics) |
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## Additional Information |
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### Dataset Curators |
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The source dataset was curated by dwb2023 and the AI Makerspace team (refer to the citation below). |
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### Licensing Information |
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This dataset is released under the MIT License. |
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### Citation Information |
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If you use this dataset in your research, please cite the [AI Makerspace team](https://aimakerspace.io/the-ai-engineering-bootcamp/). The original notebook and source data is based on their awesome course! |
