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Datasets:
Mo7art
/
Stack2Graph_VD_python

Tasks:
Feature Extraction
Question Answering
Languages:
English
Tags:
stackoverflow
qdrant
embeddings
retrieval
question-answering
License:
Dataset card Files
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Clean StackOverflow vector language dataset before upload: python

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README.md DELETED
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- ---
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- tags:
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- - vector-database
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- - embeddings
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- - parquet
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- - qdrant
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- - stackoverflow
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- - question-answering
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- pretty_name: StackOverflow Vector Dataset - Python
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- license: cc-by-sa-4.0
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- size_categories:
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- - 1M<n<10M
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- ---
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-
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- # Python StackOverflow Vector Dataset Datasheet
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-
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- ## 1. What This Dataset Is
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-
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- This dataset is the Python-specific vector shard of the Stack2Graph StackOverflow retrieval corpus.
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- Each Hugging Face dataset repository contains exactly one language dataset.
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-
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- It is optimized for dense+sparse retrieval, Qdrant restoration, and embedding-based RAG experiments.
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-
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- It is used in the Stack2Graph project as the vector counterpart to the language-scoped RDF knowledge graph shards.
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-
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- See the Stack2Graph repository for more details:
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- [https://github.com/tha-atlas/Stack2Graph](https://github.com/tha-atlas/Stack2Graph)
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-
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- ## 2. Repository Layout
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-
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- ```text
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- dataset_manifest.json
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- question_metadata_*.parquet
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- chunk_records_*.parquet
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- question_records_*.parquet
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- ```
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-
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- - `dataset_manifest.json`: language-scoped manifest for this dataset shard.
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- - `question_metadata_*.parquet`: per-question metadata and retrieval bookkeeping.
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- - `chunk_records_*.parquet`: chunk-level vector rows when parent-child indexing is enabled.
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- - `question_records_*.parquet`: question-level vector rows when chunking is disabled or exported alongside chunk data.
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-
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- ## 3. Data Model And Coverage
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-
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- The dataset is derived from Stack Overflow questions selected for the Python programming language.
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- It contains the structured records needed to rebuild the Stack2Graph Qdrant collection for that language.
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-
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- Coverage scope:
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-
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- - records are retained when they match the Stack2Graph supported language-tag set
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- - this repository contains only the Python shard
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- - the archive may contain both metadata-only and retrieval-ready vector rows depending on the export mode
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-
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- ## 4. Recommended Preprocessing
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-
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- 1. Read `dataset_manifest.json` first and use it as the source of truth for included Parquet files.
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- 2. Load all Parquet shards for this repository into your vector indexing pipeline.
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- 3. Rebuild or restore the Qdrant collection `stackoverflow_python_vector`.
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- 4. Preserve attribution and license metadata during downstream export.
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-
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- ## 5. Automatic Download And Vector DB Setup
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-
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- You do not need to regenerate embeddings from GraphDB to use this dataset.
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-
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- In the Stack2Graph repository, you can use the automation script
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- `python -m experiment.load_hf_datasets_into_services --skip-kg` to download dataset artifacts
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- and prepare the vector database service state automatically.
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-
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- Typical workflow:
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-
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- 1. Clone and configure Stack2Graph (`.env` with HF token and service paths).
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- 1. Clone and configure Stack2Graph (`.env` with HF token and service paths).
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- 1. Start required local services:
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-
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- ```bash
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- docker compose up -d
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- ```
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-
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- 1. Run the loader script:
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-
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- ```bash
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- python -m experiment.load_hf_datasets_into_services --skip-kg
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- ```
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-
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- For manual usage without automation, directly ingest the listed Parquet files into your vector database.
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-
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- ## 6. Quality Notes And Caveats
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-
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- - A Stack Overflow question may belong to multiple language shards when tagged with multiple languages.
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- - Embeddings and sparse representations depend on the configured export pipeline and model versions.
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- - As with community-generated data, content may include noise, bias, and temporal drift.
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-
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- ## 7. Intended Use
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-
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- - semantic retrieval and reranking
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- - RAG and hybrid retriever experiments
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- - vector database benchmarking and diagnostics
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- - language-scoped developer tooling research
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-
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- ## 8. Limitations
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-
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- - Not a complete mirror of all Stack Overflow content.
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- - Not all export modes include the same row types or chunk layouts.
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- - Best used together with the Stack2Graph retrieval pipeline and Qdrant-compatible tooling.
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-
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- ## 9. Licensing And Attribution
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-
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- This dataset inherits Stack Overflow source licensing and attribution requirements.
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- Ensure compliant attribution and redistribution practices in all derived artifacts.
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-
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- ## 10. Suggested Citation
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-
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- If you use this dataset, cite the Stack2Graph work:
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-
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- - Stack2Graph: A Structured Knowledge Representation of Stack Overflow Data for Retrieval-based Question Answering
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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