Datasets:
| license: mit | |
| task_categories: | |
| - text-generation | |
| language: | |
| - en | |
| tags: | |
| - domain-specific | |
| - filtered-corpus | |
| - ontology-guided | |
| size_categories: | |
| - unknown | |
| # quantum-physics-0.6 | |
| ## Dataset Description | |
| This is a domain-specific corpus created using ontology-guided filtering from FineWeb-Edu. | |
| ### Dataset Creation | |
| - **Source:** HuggingFaceFW/fineweb-edu | |
| - **Filtering Method:** Semantic similarity to subdomain centroids (embedding-based) | |
| - **Pipeline:** Ontology-Guided Domain Corpus Builder | |
| ### Dataset Structure | |
| Each chunk contains: | |
| - `text`: The text content (256-512 tokens) | |
| - `subdomain_id`: Assigned subdomain | |
| - `similarity_score`: Cosine similarity to subdomain centroid | |
| - `token_count`: Number of tokens | |
| - `source_dataset`: Original dataset name | |
| - `source_id`: Original document ID | |
| - `chunk_index`: Position within source document | |
| ### Usage | |
| ```python | |
| from datasets import load_dataset | |
| dataset = load_dataset("konsman/quantum-physics-0.6") | |
| # Access filtered chunks | |
| for chunk in dataset['train']: | |
| print(chunk['text']) | |
| print(chunk['subdomain_id']) | |
| print(chunk['similarity_score']) | |
| ``` | |
| ### License | |
| MIT License | |
| ### Citation | |
| Generated using the Ontology-Guided Domain Corpus Builder pipeline. | |