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Transformation of raw datasets into structured formats containing task descriptions and dynamic schemas.
Distinct from Data Conversion Utilities: Focuses on converting data into LLM-ready instruction formats rather than simple data cleaning.
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DeepKE is a knowledge extraction toolkit and framework designed to transform unstructured text into structured knowledge graphs. It provides a pipeline for identifying and classifying named entities, semantic relations, and events, converting raw datasets into structured triples. The project utilizes large language models as tool callers through a standardized context protocol to drive automated data extraction processes. It supports schema-driven extraction across multiple domains and bilingual text, employing joint entity and relation extraction to identify components in a single structured
Transforms raw extraction datasets into structured formats featuring task descriptions and dynamic schemas.