Title: An algorithm to generate short sentences in natural language from linked open data based on linguistic templates

Authors: Augusto Lopes Da Silva; Sandro José Rigo; Jéssica Braun De Moraes

Addresses: Universidade do Vale do Rio dos Sinos, São Leopoldo, Rio Grande do Sul, Brazil ' Universidade do Vale do Rio dos Sinos, São Leopoldo, Rio Grande do Sul, Brazil ' Universidade do Vale do Rio dos Sinos, São Leopoldo, Rio Grande do Sul, Brazil

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.

Keywords: linked open data; natural language generation; RDF; ontologies; linguistic templates; fluency.

DOI: 10.1504/IJMSO.2020.112798

International Journal of Metadata, Semantics and Ontologies, 2020 Vol.14 No.3, pp.197 - 208

Received: 07 Mar 2020
Accepted: 31 Jul 2020

Published online: 26 Jan 2021 *

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