Summary of Towards Automatic Composition Of Asp Programs From Natural Language Specifications, by Manuel Borroto et al.
Towards Automatic Composition of ASP Programs from Natural Language Specifications
by Manuel Borroto, Irfan Kareem, Francesco Ricca
First submitted to arxiv on: 7 Mar 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: None
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary A novel paper proposes a significant step towards automating the composition of Answer Set Programming (ASP) specifications, focusing on graph-related problem specifications. The contributions include a dataset designed to develop and assess tools for automatic ASP coding, as well as a two-step architecture implemented in NL2ASP, a tool that generates ASP programs from natural language specifications. This approach utilizes neural machine translation to transform natural language into Controlled Natural Language (CNL) statements, which are then converted into ASP code using CNL2ASP. Experimental results confirm the viability of this method. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper helps machines write special kinds of computer codes called Answer Set Programming (ASP) specifications. The researchers made a dataset with examples of graph problems to test and improve tools that can automatically create ASP codes. They also created an architecture for their tool, NL2ASP, which takes natural language descriptions and turns them into ASP code. This is done in two steps: first, using neural machines to translate natural language into a special language called Controlled Natural Language (CNL), then converting CNL into ASP. |
Keywords
» Artificial intelligence » Translation
