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LogicLM: Robust Application of Large Language Models with Logic Programming for Data Analytics

  • Evgeny Skvortsovc(Author)
    ,
  • Shayan Mirjafaric(Author)
    ,
  • Ojaswa Gargc(Author)
    ,
  • Yilin Xiab(Author)
    ,
  • Shawn Bowersa(Author)
    ,
  • Bertram Ludäscherb(Author)
Research Output: Contribution to conference Paper

Open access

Abstract

We present LogicLM, an OLAP-style interactive data analysis system that leverages large language models (LLMs) and is configured using Logica, an enhanced logic programming language with aggregation support that compiles to SQL. LogicLM uses an LLM to translate natural language queries by end users into executable code for automatically generating data visualizations. For each natural-language query, LogicLM provides a verifiable OLAP-based configuration that users can view and modify to help ensure results are reliable and accurate. This configuration, with measures, dimensions, and filters defined as logical predicates, offers a unified and user-friendly approach to naturallanguage data exploration, while keeping end users in control of the analysis process.