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For example, in a report, character A and character B participate in an activity together. When extracting kag, it can establish a "possible_recognize" relationship between character A and character B. Is there a way to achieve such reasoning?
The text was updated successfully, but these errors were encountered:
For example, in a report, character A and character B participate in an activity together. When extracting kag, it can establish a "possible_recognize" relationship between character A and character B. Is there a way to achieve such reasoning?
Link prediction is a classic problem in the field of knowledge graph.
The goal of KAG-Builder is to build knowledge graph from docs, and then most of (gnn algorithm / pattern matching algorithm ) can be applied in KAG-Solver.
For example, in a report, character A and character B participate in an activity together. When extracting kag, it can establish a "possible_recognize" relationship between character A and character B. Is there a way to achieve such reasoning?
Link prediction is a classic problem in the field of knowledge graph. The goal of KAG-Builder is to build knowledge graph from docs, and then most of (gnn algorithm / pattern matching algorithm ) can be applied in KAG-Solver.
I understand that the solver module is mainly for intelligent QA. Does it mean that the solver module extracts the character reasoning relationship by constructing prompts and then writes it into the graph?
For example, in a report, character A and character B participate in an activity together. When extracting kag, it can establish a "possible_recognize" relationship between character A and character B. Is there a way to achieve such reasoning?
The text was updated successfully, but these errors were encountered: