# CNL2ASP: converting controlled natural language sentences into ASP

arXiv: https://arxiv.org/abs/2311.10505 · HTML: https://mlsanity.com/paper/2311.10505/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- Builds on 7 of its 14 references that are in the map.
- First posted on arXiv 17 Nov 2023.

## Builds on (most cited first, 7 of 7)

- [ASP-Core-2 Input Language Format](https://mlsanity.com/paper/1911.04326/) (2019)
- [A Survey and Classification of Controlled Natural Languages](https://mlsanity.com/paper/1507.01701/) (2015)
- [Clingcon: The Next Generation](https://mlsanity.com/paper/1705.04569/) (2017)
- [An ASP-based Solution to the Chemotherapy Treatment Scheduling problem](https://mlsanity.com/paper/2108.02637/) (2021)
- [Manipulation of Articulated Objects using Dual-arm Robots via Answer Set Programming](https://mlsanity.com/paper/2010.01164/) (2020)
- [Towards Metric Temporal Answer Set Programming](https://mlsanity.com/paper/2008.02038/) (2020)
- [Specifying and Verbalising Answer Set Programs in Controlled Natural Language](https://mlsanity.com/paper/1804.10765/) (2018)

## Built on by (most cited first, 5 of 5)

- [LLASP: Fine-tuning Large Language Models for Answer Set Programming](https://mlsanity.com/paper/2407.18723/) (2024)
- [Towards Automatic Composition of ASP Programs from Natural Language Specifications](https://mlsanity.com/paper/2403.04541/) (2024)
- [Bridging Natural Language and ASP: A Hybrid Approach Using LLMs and AMR Parsing](https://mlsanity.com/paper/2511.08715/) (2025)
- [ASP-Bench: From Natural Language to Logic Programs](https://mlsanity.com/paper/2602.01171/) (2026)
- [BLAST: Benchmarking LLMs with ASP-based Structured Testing](https://mlsanity.com/paper/2604.22306/) (2026)

## Abstract (arXiv)

Answer Set Programming (ASP) is a popular declarative programming language for solving hard combinatorial problems. Although ASP has gained widespread acceptance in academic and industrial contexts, there are certain user groups who may find it more advantageous to employ a higher-level language that closely resembles natural language when specifying ASP programs. In this paper, we propose a novel tool, called CNL2ASP, for translating English sentences expressed in a controlled natural language (CNL) form into ASP. In particular, we first provide a definition of the type of sentences allowed by our CNL and their translation as ASP rules, and then exemplify the usage of the CNL for the specification of both synthetic and real-world combinatorial problems. Finally, we report the results of an experimental analysis conducted on the real-world problems to compare the performance of automatically generated encodings with the ones written by ASP practitioners, showing that our tool can obtain satisfactory performance on these benchmarks. Under consideration in Theory and Practice of Logic Programming (TPLP).