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--- |
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license: cc-by-4.0 |
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task_categories: |
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- text-generation |
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- feature-extraction |
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language: |
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- en |
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tags: |
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- rdf |
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- knowledge-graph |
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- semantic-web |
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- triples |
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size_categories: |
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- 1K<n<10K |
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--- |
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# WordNet RDF |
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## Dataset Description |
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Lexical database of semantic relations between words (English WordNet 2024) |
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**Original Source:** https://en-word.net/static/english-wordnet-2024.ttl.gz |
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### Dataset Summary |
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This dataset contains RDF triples from WordNet RDF converted to HuggingFace |
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dataset format for easy use in machine learning pipelines. |
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- **Format:** Originally turtle, converted to HuggingFace Dataset |
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- **Size:** 0.21 GB (extracted) |
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- **Entities:** ~120K synsets |
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- **Triples:** ~2M |
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- **Original License:** CC BY 4.0 |
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### Recommended Use |
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Quick validation, linguistic relationships, small-scale testing |
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### Notes |
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Compressed download, automatic extraction. English WordNet 2024 from en-word.net |
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## RDF Format |
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This dataset uses a standard lossless format for representing RDF triples. Each triple is a row with 6 fields: |
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- `subject`: Subject URI or blank node |
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- `predicate`: Predicate URI |
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- `object`: Object value (URI, literal, or blank node) |
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- `object_type`: Type of object (`uri`, `literal`, or `blank_node`) |
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- `object_datatype`: XSD datatype URI (for typed literals) |
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- `object_language`: Language tag (for language-tagged literals) |
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### Loading the Dataset |
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```python |
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from datasets import load_dataset |
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dataset = load_dataset("wordnet") |
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for row in dataset["train"]: |
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print(f"{row['subject']} {row['predicate']} {row['object']}") |
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``` |
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## Citation |
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If you use this dataset, please cite the original source: |
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**Dataset:** WordNet RDF |
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**URL:** https://en-word.net/static/english-wordnet-2024.ttl.gz |
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**License:** CC BY 4.0 |
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## Conversion Details |
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- **Converted using:** [RDF to HuggingFace Incremental Converter](https://github.com/CleverThis/cleverernie) |
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- **Conversion date:** 2026-01-13 |
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- **Format version:** 1.0 |
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--- |
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This dataset is part of the CleverThis knowledge graph collection. |
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