RDF2PT: Generating Brazilian Portuguese Texts from RDF Data
This work addresses a domain-specific need for generating Brazilian Portuguese from RDF data, but it is incremental as it adapts existing methods to a new language.
The authors tackled the problem of generating Brazilian Portuguese texts from RDF data, a gap in existing research, and found that RDF2PT produces text similar to human-generated output, as evaluated by 44 native speakers.
The generation of natural language from Resource Description Framework (RDF) data has recently gained significant attention due to the continuous growth of Linked Data. A number of these approaches generate natural language in languages other than English, however, no work has been proposed to generate Brazilian Portuguese texts out of RDF. We address this research gap by presenting RDF2PT, an approach that verbalizes RDF data to Brazilian Portuguese language. We evaluated RDF2PT in an open questionnaire with 44 native speakers divided into experts and non-experts. Our results suggest that RDF2PT is able to generate text which is similar to that generated by humans and can hence be easily understood.