The invention relates to the technical field of
semantic network reasoning, in particular to a
knowledge base and map collaborative enhancement
large model reasoning system and method, and the
system comprises a structure guiding module, a
semantic difference module, a stability extraction module, a path comparison module and a
label binding module. According to the method, graph path node semantic vectors and channel numbers are extracted, response entity fitting degrees and sequences are combined, structured distribution information is constructed, semantic
path recognition precision is enhanced, difference entities are screened on the basis of semantic distances, and stability parameters are generated in combination with context word frequencies, co-occurrence frequencies and document distribution; semantic conflicts are positioned,
paragraph stability is quantified, alignment of semantic contents and structural paths is achieved, causal chain consistency is improved, the relation between response paragraphs and path nodes is marked, traceable chains are formed, reasoning transparency and result verifiability are enhanced, and semantic calculation,
structure extraction, sequence judgment and other means are fused. And the reasoning accuracy,
interpretability and credibility are improved.