An algorithm to generate short sentences in natural language from linked open data based on linguistic templates. (26th January 2021)

• Record Type: Journal Article
• Authors: Silva, Augusto Lopes Da; Rigo, Sandro José; Moraes, Jéssica Braun De
• Is Part Of: International journal of metadata, semantics and ontologies. Volume 14:Number 3(2020)
• Page Start: 197
• Page End: 208
• Publication Date: 2021-01-26
• Subjects: linked open data -- natural language generation -- RDF -- ontologies -- linguistic templates -- fluency; Metadata -- Periodicals; Semantic Web -- Periodicals; Ontologies (Information retrieval) -- Periodicals; Data structures (Computer science) -- Periodicals; Information theory -- Periodicals; 005.74
• Languages: English
• ISSNs: 1744-2621

Abstract

The generation of natural language phrases from Linked Open Data can benefit from a significant amount of information available on the internet, as well as from the existence of properties within them, which appears, mostly, in the RDF format. These properties can represent semantic relationships between concepts that might help in creating sentences in natural language. Nevertheless, research in this field tends not to use the information in RDF. We support that this is a factor that might foster the generation of more natural phrases. In this scenario, this research explores these RDF properties for the generation of natural language phrases. The short sentences generated by the algorithm implementation were evaluated regarding their fluency by linguists and native English speakers. The results show that the sentences generated are promising regarding sentence fluency.