Metadata Reasoner uses agentic LLM reasoning on metadata to select sufficient and minimal data sources, achieving 83.16% F1 on KramaBench and 85.5% F1 on noisy synthetic benchmarks while avoiding low-quality tables 99% of the time.
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A three-phase roadmap formalizes multi-database reasoning for Text2Cypher to handle questions spanning independent graph databases.
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An Agentic Approach to Metadata Reasoning
Metadata Reasoner uses agentic LLM reasoning on metadata to select sufficient and minimal data sources, achieving 83.16% F1 on KramaBench and 85.5% F1 on noisy synthetic benchmarks while avoiding low-quality tables 99% of the time.
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Toward Multi-Database Query Reasoning for Text2Cypher
A three-phase roadmap formalizes multi-database reasoning for Text2Cypher to handle questions spanning independent graph databases.