Summary of Large Language Models As Oracles For Instantiating Ontologies with Domain-specific Knowledge, by Giovanni Ciatto and Andrea Agiollo and Matteo Magnini and Andrea Omicini
Large language models as oracles for instantiating ontologies with domain-specific knowledge
by Giovanni Ciatto, Andrea Agiollo, Matteo Magnini, Andrea Omicini
First submitted to arxiv on: 5 Apr 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Computation and Language (cs.CL); Information Retrieval (cs.IR); Machine Learning (cs.LG); Logic in Computer Science (cs.LO)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This AI research paper proposes an innovative approach to automatically instantiate ontologies with domain-specific knowledge, utilizing large language models (LLMs) as oracles. The authors aim to mitigate the time-consuming, error-prone, and biased process of manual ontology design by leveraging LLMs for query-based instance generation. Starting from a schema and query templates, the method queries the LLM multiple times to generate instances for classes and properties, effectively populating the ontology with domain-specific knowledge. The authors formalize their approach and instantiate it over various LLMs, including a concrete case study in the nutritional domain where they evaluate the quality of generated ontologies. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper creates an automatic way to add information to special dictionaries called ontologies using large language models (LLMs). Right now, experts have to do this work by hand, which can take a long time and might not be accurate. The authors want to change this by asking the LLM for help. They start with a basic structure for their ontology and some questions about what should go in it. Then they ask the LLM many times to give them examples of things that fit into these categories, and use those examples to fill in the rest of the dictionary. |
