RDFjsRealB: a Symbolic Approach for Generating Text from RDF Triples

Abstract

This paper describes the Resource Description Framework (RDF) triples verbalizer developed for the WEB NLG CHALLENGE 2020 shared task. After reviewing representative works in Natural Language Generation in the context of the Semantic Web, the task is then described. We then sketch the symbolic approach we used for verbalizing RDF triples: once the triples are grouped by subject, each group is realized as one or more sentences using templates written in Python whose output is feed to an English realizer written in Javascript. The system was developed using the test data of the previous edition of the task and the train and development data of this year’s task. The automatic scores for this year’s test data are quite competitive. We conclude with a critical review of the data and discuss the suitability of this competition results in a wider Natural Language Generation setting.

Tasks

Reproductions