2014/04/29 by Edward Grefenstette, Grefenstette, Edward, Phil Blunsom +5 · 1 citation
Computer Science · #Computation and Language (cs.CL) #FOS: Computer and information sciences #Natural Language Processing Techniques #Semantic Web and Ontologies #Topic Modeling #cs.CL
paper · pdf · doi:10.48550/arxiv.1404.7296
In Proceedings of the Semantic Parsing Workshop at ACL 2014 (forthcoming)
arxiv created 2014/04/29 · openalex publication_date 2014/04/29 · arxiv updated 2014/04/30 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Many successful approaches to semantic parsing build on top of the syntactic analysis of text, and make use of distributional representations or statistical models to match parses to ontology-specific queries. This paper presents a novel deep learning architecture which provides a semantic parsing system through the union of two neural models of language semantics. It allows for the generation of ontology-specific queries from natural language statements and questions without the need for parsing, which makes it especially suitable to grammatically malformed or syntactically atypical text, such as tweets, as well as permitting the development of semantic parsers for resource-poor languages.