The 2020 Bilingual, Bi-Directional WebNLG+ Shared Task Overview and Evaluation Results (WebNLG+ 2020)
Year: 2020
Type: conference-paper
Abstract: WebNLG+ offers two challenges: (i) mapping sets of RDF triples to English or Russian text (generation) and (ii) converting English or Russian text to sets of RDF triples (semantic parsing). Compared to the eponymous WebNLG challenge, WebNLG+ provides an extended dataset that enable the training, evaluation, and comparison of microplanners and semantic parsers. In this paper, we present the results of the generation and semantic parsing task for both English and Russian and provide a brief description of the participating systems.
Institutions: Universidade Federal de Minas Gerais, Centre National de la Recherche Scientifique, Laboratoire Lorrain de Recherche en Informatique et ses Applications, Chalmers University of Technology, University of Gothenburg, Tilburg University, Universitat Pompeu Fabra, Paderborn University, Université de Lorraine
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W3131933120