ReLTEx combines LLM candidate generation with a path-aware validity classifier and recursive stopping, recovering up to 44% (SemEval) and 23% (Schema.org) of masked concepts with high human-rated coherence of accepted nodes.
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ReLTEx: Reliable LLM-based Taxonomy Expansion
ReLTEx combines LLM candidate generation with a path-aware validity classifier and recursive stopping, recovering up to 44% (SemEval) and 23% (Schema.org) of masked concepts with high human-rated coherence of accepted nodes.