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NABU - Multilingual Graph-based Neural RDF Verbalizer [article]

Diego Moussallem and Dwaraknath Gnaneshwar and Thiago Castro Ferreira and Axel-Cyrille Ngonga Ngomo
2020 arXiv   pre-print
We address this research gap by presenting NABU, a multilingual graph-based neural model that verbalizes RDF data to German, Russian, and English.  ...  NABU is based on an encoder-decoder architecture, uses an encoder inspired by Graph Attention Networks and a Transformer as decoder.  ...  Despite the plethora of graph-based neural approaches on handling RDF data, English is the only language which has been widely targeted.  ... 
arXiv:2009.07728v2 fatcat:a3aqjv6ubrf4hhdpl4tlfx5t2e

Bridging the Gap Between Ontology and Lexicon via Class-Specific Association Rules Mined from a Loosely-Parallel Text-Data Corpus

Basil Ell, Mohammad Fazleh Elahi, Philipp Cimiano, Dagmar Gromann, Gilles Sérasset, Thierry Declerck, John P. McCrae, Jorge Gracia, Julia Bosque-Gil, Fernando Bobillo, Barbara Heinisch
2021
There is a well-known lexical gap between content expressed in the form of natural language (NL) texts and content stored in an RDF knowledge base (KB).  ...  For tasks such as Natural Language Generation, this gap needs to be bridged from KB to NL, so that facts stored in an RDF KB can be verbalized and read by humans.  ...  NABU-Multilingual Graph-Based Neural RDF Verbalizer. In ISWC, pages 420-437, 2020. 12 Diego Moussallem, René Speck, and Axel-Cyrille Ngonga Ngomo.  ... 
doi:10.4230/oasics.ldk.2021.33 fatcat:v3dimcw7kfgwbji72lqkc2nvfi