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Fabrizio Lo Scudo

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Open access Sep 2026

Integrating Answer Set Programming and Large Language Models for Reliable Structured Knowledge Extraction

Answer Set Programming (ASP) and Large Language Models (LLMs) offer complementary strengths in symbolic reasoning and natural language understanding. In this work, we present an integrated framework for reliable structured knowledge extraction from natural language that combines the syntactic capabilities of LLMs with...

Mario Alviano, Matteo Capalbo, G. Gottlob et al. · 0 citations
Open access Jun 2026

Logic-Guided Data Extraction with Answer Set Programming and Large Language Models

A logic-guided data extraction framework combining LLM-based extraction with answer set programming (ASP), which reduces LLM calls and improves extraction quality by mitigating spurious outputs, demonstrating the value of non-monotonic logic programming for controlled semantic extraction.

Mario Alviano, Lorenzo Grillo, N. Leone et al. · 1 citation

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