ScrapeGraphAI-100k: Dataset for Schema-Constrained LLM Generation
Learn about ScrapeGraphAI-100k, a dataset for schema-constrained LLM generation, and how to apply it to improve tool use and structured extraction in large language models
- Collect and preprocess the ScrapeGraphAI-100k dataset using Python and relevant libraries
- Apply schema-constrained generation techniques to the dataset using LLMs and evaluate their performance
- Use the dataset to fine-tune LLMs for tool use and structured extraction tasks, such as JSON schema generation
- Compare the performance of different LLMs on the dataset using metrics like accuracy and F1-score
- Integrate the dataset into existing NLP pipelines to improve knowledge base construction and information extraction
NLP engineers and researchers can benefit from this dataset to develop and fine-tune their models for schema-constrained generation tasks, while data scientists can utilize it to improve knowledge base construction and structured extraction
💡 ScrapeGraphAI-100k provides a large-scale dataset for schema-constrained LLM generation, enabling researchers and practitioners to develop more accurate and efficient models for tool use and structured extraction
🚀 Introducing ScrapeGraphAI-100k, a dataset for schema-constrained LLM generation! 🤖 Improve tool use and structured extraction in your NLP models with this new resource 📈
Key Takeaways
Learn about ScrapeGraphAI-100k, a dataset for schema-constrained LLM generation, and how to apply it to improve tool use and structured extraction in large language models
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Abstract:
arXiv:2602.15189v2 Announce Type: replace-cross Abstract: Producing output that conforms to a specified JSON schema underlies tool use, structured extraction, and knowledge base construction in modern large language models. Despite this centrality, public datasets for the task remain small, synthetic, or text-only, and rarely pair real page content with the prompts and schemas used in practice. We introduce ScrapeGraphAI-100k, 93,695 schema-constrained extraction events collected via opt-in Scra
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