ArticleBioinformatics (Oxford, England)2024
Structured Prompt Interrogation and Recursive Extraction of Semantics (SPIRES): a method for populating knowledge bases using zero-shot learning.
Article in Bioinformatics (Oxford, England), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 papers.
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Who cites it
45 citing papers in PubMed.
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- RescueGPT: An Automated System for Detecting Adverse Safety Events in Prehospital Emergency Medical Service Notes With a Zero-Shot Approach With Large Language Models: A Proof-of-Concept Study.Learning health systems · 2026Article
- The Cell Ontology in the age of single-cell omics.Scientific data · 2026Article
- Inflammation significantly alters mucosal transcriptomic signatures in pediatric inflammatory bowel disease.Crohn's & colitis 360 · 2026Article
- A custom phenotypic profile for Fanconi anemia: Addressing gaps in existing disease annotations.medRxiv : the preprint server for health sciences · 2026Article
- Assessing the effectiveness of ontology-grounded AI term extraction using OntoGPT for environmental evidence synthesis.Environmental evidence · 2026Article
- Computational strategies for cross-species knowledge transfer.Nature methods · 2026Review
- LinkML: an open data modeling framework.GigaScience · 2026Article
- Rosetta Statements: simplifying FAIR knowledge graph construction with a user-centred approach.Database : the journal of biological databases and curation · 2026Article
- The Gene Ontology knowledgebase in 2026.Nucleic acids research · 2026Article
- GOFlowLLM-curating miRNA literature with large language models and flowcharts.Bioinformatics (Oxford, England) · 2026Article
- Comparative Analysis of Generative AI Language Models in Orthodontics: Evidence-Based Insights Into Perplexity, iASK, and ChatGPT 4o Mini.TheScientificWorldJournal · 2026Article
- SPARROW: subtyping Parkinson's disease with agentic reasoning and robust omics workflow.NPJ artificial intelligence · 2026Article
- Using GPT-4 to annotate the severity of all phenotypic abnormalities within the human phenotype ontology.Frontiers in digital health · 2026Article
- Large Language Models in Bio-Ontology Research: A Review.Bioengineering (Basel, Switzerland) · 2025Review
- Introducing mCODEGPT as a zero-shot information extraction from clinical free text data tool for cancer research.Communications medicine · 2025Article
- Probing the limitations of multimodal language models for chemistry and materials research.Nature computational science · 2025Article
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Authors and funding
12 authors.
Funding
Abstract
motivationCreating knowledge bases and ontologies is a time consuming task that relies on manual curation. AI/NLP approaches can assist expert curators in populating these knowledge bases, but current approaches rely on extensive training data, and are not able to populate arbitrarily complex nested knowledge schemas.
resultsHere we present Structured Prompt Interrogation and Recursive Extraction of Semantics (SPIRES), a Knowledge Extraction approach that relies on the ability of Large Language Models (LLMs) to perform zero-shot learning and general-purpose query answering from flexible prompts and return information conforming to a specified schema. Given a detailed, user-defined knowledge schema and an input text, SPIRES recursively performs prompt interrogation against an LLM to obtain a set of responses matching the provided schema. SPIRES uses existing ontologies and vocabularies to provide identifiers for matched elements. We present examples of applying SPIRES in different domains, including extraction of food recipes, multi-species cellular signaling pathways, disease treatments, multi-step drug mechanisms, and chemical to disease relationships. Current SPIRES accuracy is comparable to the mid-range of existing Relation Extraction methods, but greatly surpasses an LLM's native capability of grounding entities with unique identifiers. SPIRES has the advantage of easy customization, flexibility, and, crucially, the ability to perform new tasks in the absence of any new training data. This method supports a general strategy of leveraging the language interpreting capabilities of LLMs to assemble knowledge bases, assisting manual knowledge curation and acquisition while supporting validation with publicly-available databases and ontologies external to the LLM. AVAILABILITY AND IMPLEMENTATION: SPIRES is available as part of the open source OntoGPT package: https://github.com/monarch-initiative/ontogpt.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.