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Structured Prompt Interrogation and Recursive Extraction of Semantics (SPIRES): a method for populating knowledge

J Harry Caufield1, Harshad Hegde1, Vincent Emonet2

  • 1Biosystems Data Science, Division of Environmental Genomics and Systems Biology, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, United States.

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|February 21, 2024
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Structured Prompt Interrogation and Recursive Extraction of Semantics (SPIRES) automates knowledge base creation using Large Language Models (LLMs). This AI approach extracts complex information without extensive training data, aiding manual curation.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Knowledge Representation

Background:

  • Manual curation of knowledge bases and ontologies is labor-intensive.
  • Existing AI/NLP methods require substantial training data and struggle with complex schemas.

Purpose of the Study:

  • To introduce Structured Prompt Interrogation and Recursive Extraction of Semantics (SPIRES), an AI-driven approach for knowledge extraction.
  • To leverage Large Language Models (LLMs) for zero-shot learning in populating knowledge bases with complex, nested schemas.

Main Methods:

  • SPIRES utilizes LLMs for zero-shot learning and flexible prompt-based querying.
  • It recursively interrogates LLMs with user-defined schemas to extract information and match specified formats.
  • The system integrates existing ontologies and vocabularies to ground extracted entities with unique identifiers.

Main Results:

  • SPIRES demonstrates successful application across diverse domains, including recipes, cellular pathways, and disease treatments.
  • Achieves accuracy comparable to mid-range Relation Extraction methods.
  • Significantly enhances an LLM's ability to ground entities with unique identifiers.

Conclusions:

  • SPIRES offers a flexible, customizable method for knowledge base assembly, requiring no new training data for novel tasks.
  • It effectively leverages LLM capabilities to support and accelerate manual knowledge curation.
  • The approach facilitates validation against external databases and ontologies.