Knowledge graph triples are generated by providing prompts to LLMs. Due to constraints like context length and the need for better output quality, the unstructured text is processed in smaller chunks rather than all at once. As a result, a large amount of fragmented graph data is produced. In this scenario, the processes of collating, deduplicating, and eliminating similar relations and entities become crucial to ensure accuracy and efficiency.
Expected Output
A deduplicated and consolidated knowledge graph with unique entities and relations, ensuring clarity and eliminating redundancy.
Description
Knowledge graph triples are generated by providing prompts to LLMs. Due to constraints like context length and the need for better output quality, the unstructured text is processed in smaller chunks rather than all at once. As a result, a large amount of fragmented graph data is produced. In this scenario, the processes of collating, deduplicating, and eliminating similar relations and entities become crucial to ensure accuracy and efficiency.
Expected Output
A deduplicated and consolidated knowledge graph with unique entities and relations, ensuring clarity and eliminating redundancy.
Implementation Plan