mlsanityData to 7 Oct 2026

Towards Automatic Composition of ASP Programs from Natural Language Specifications

arXiv 2403.04541 ↗First posted 7 Mar 2024cs.AIcited by 7

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Abstract (arXiv)

This paper moves the first step towards automating the composition of Answer Set Programming (ASP) specifications. In particular, the following contributions are provided: (i) A dataset focused on graph-related problem specifications, designed to develop and assess tools for ASP automatic coding; (ii) A two-step architecture, implemented in the NL2ASP tool, for generating ASP programs from natural language specifications. NL2ASP uses neural machine translation to transform natural language into Controlled Natural Language (CNL) statements. Subsequently, CNL statements are converted into ASP code using the CNL2ASP tool. An experiment confirms the viability of the approach.

Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). Builds on 22 of its 56 references that are in the map. First posted on arXiv 7 Mar 2024.

Builds on

22 of 56 references.

References · 22

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10 more
  1. 2018A Skeleton-Based Model for Promoting Coherence Among Sentences in Narrative Story Generationcited by 42
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Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 1; 2025: 2; 2026: 4.

7 papers.

  1. 2024LLASP: Fine-tuning Large Language Models for Answer Set Programmingcited by 8
  2. 2025Can LLMs Solve ASP Problems? Insights from a Benchmarking Study (Extended Version)cited by 1
  3. 2025Bridging Natural Language and ASP: A Hybrid Approach Using LLMs and AMR Parsingcited by 0
  4. 2026XAI-LAW: A Logic Programming Tool for Modeling, Explaining, and Learning Legal Decisionscited by 0
  5. 2026ASP-Bench: From Natural Language to Logic Programscited by 0
  6. 2026Streamliners for Answer Set Programmingcited by 0
  7. 2026BLAST: Benchmarking LLMs with ASP-based Structured Testingcited by 0