A Case Study of NLG from Multimedia Data Sources: Generating Architectural Landmark Descriptions

ACL (WebNLG, INLG) 2020  ·  Simon Mille, Spyridon Symeonidis, Maria Rousi, Montserrat Marimon Felipe, Klearchos Stavrothanasopoulos, Petros Alvanitopoulos, Roberto Carlini Salguero, Jens Grivolla, Georgios Meditskos, Stefanos Vrochidis, Leo Wanner ·

In this paper, we present a pipeline system that generates architectural landmark descriptions using textual, visual and structured data. The pipeline comprises five main components:(i) a textual analysis component, which extracts information from Wikipedia pages; (ii)a visual analysis component, which extracts information from copyright-free images; (iii) a retrieval component, which gathers relevant (property, subject, object) triples from DBpedia; (iv) a fusion component, which stores the contents from the different modalities in a Knowledge Base (KB) and resolves the conflicts that stem from using different sources of information; (v) an NLG component, which verbalises the resulting contents of the KB. We show that thanks to the addition of other modalities, we can make the verbalisation of DBpedia triples more relevant and/or inspirational.

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