Summary of the paper

Title RDF2PT: Generating Brazilian Portuguese Texts from RDF Data
Authors Diego Moussallem, Thiago Ferreira, Marcos Zampieri, Maria Cláudia Cavalcanti, Geraldo Xexéo, Mariana Neves and Axel-Cyrille Ngonga Ngomo
Abstract The generation of natural language from 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.
Topics Summarisation, Semantic Web, Natural Language Generation
Full paper RDF2PT: Generating Brazilian Portuguese Texts from RDF Data
Bibtex @InProceedings{MOUSSALLEM18.783,
  author = {Diego Moussallem and Thiago Ferreira and Marcos Zampieri and Maria Cláudia Cavalcanti and Geraldo Xexéo and Mariana Neves and Axel-Cyrille Ngonga Ngomo},
  title = "{RDF2PT: Generating Brazilian Portuguese Texts from RDF Data}",
  booktitle = {Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018)},
  year = {2018},
  month = {May 7-12, 2018},
  address = {Miyazaki, Japan},
  editor = {Nicoletta Calzolari (Conference chair) and Khalid Choukri and Christopher Cieri and Thierry Declerck and Sara Goggi and Koiti Hasida and Hitoshi Isahara and Bente Maegaard and Joseph Mariani and Hélène Mazo and Asuncion Moreno and Jan Odijk and Stelios Piperidis and Takenobu Tokunaga},
  publisher = {European Language Resources Association (ELRA)},
  isbn = {979-10-95546-00-9},
  language = {english}
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