{"type":"ScholarlyArticle","title":"Towards Automatic Composition of ASP Programs from Natural Language Specifications","authors":[{"name":"Manuel Borroto Santana","slug":"manuel-borroto-santana","given":"Manuel","family":"Borroto Santana","affiliation":"Department of Mathematics and Computer Science , University of Calabria , Rende CS , 87036 , Italy"},{"name":"Irfan Kareem","slug":"irfan-kareem","given":"Irfan","family":"Kareem","affiliation":"Department of Mathematics and Computer Science , University of Calabria , Rende CS , 87036 , Italy"},{"name":"Francesco Ricca","slug":"francesco-ricca","given":"Francesco","family":"Ricca","affiliation":"Department of Mathematics and Computer Science , University of Calabria , Rende CS , 87036 , Italy"}],"abstract":"This paper moves the first step towards automating the composition of Answer Set Programming (ASP) specifications.\r\nIn particular, the following contributions are provided: \r\n(i) A dataset focused on graph-related problem specifications, designed to develop and assess tools for ASP automatic coding;\r\n(ii) A two-step architecture, implemented in the NL2ASP tool, for generating ASP programs from natural language specifications.\r\nNL2ASP 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 experimental analysis confirms the viability of the approach.","doi":"10.24963/ijcai.2024/685","url":"https://ijcai.org/proceedings/2024/685","pdf":"https://ijcai.org/proceedings/2024/0685.pdf","markdown":"https://ijcai.org/proceedings/2024/685.md","bibtex":"https://ijcai.org/proceedings/2024/bibtex/685","volume":{"slug":"2024","title":"Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2024","url":"https://ijcai.org/proceedings/2024/","year":2024,"location":"Jeju, Korea","dates":"3-9 August 2024","editors":"Kate Larson","isbn":"978-1-956792-04-1","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2024"},"section":"Natural Language Processing","track":"Main Track","number":685,"pages":{"first":6198,"last":6206},"keywords":["Machine Learning: ML: Generative models","Knowledge Representation and Reasoning: KRR: Logic programming","Natural Language Processing: NLP: Applications"],"videos":[],"references":[{"position":1,"raw":"[Alviano et al., 2017] Mario Alviano, Francesco Calimeri, Carmine Dodaro, Davide Fuscà, Nicola Leone, Simona Perri, Francesco Ricca, Pierfrancesco Veltri, and Jessica Zangari. 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