| 1. |
- Castro Ferreira, Thiago, et al.
(författare)
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The 2020 Bilingual, Bi-Directional WebNLG+ Shared Task Overview and Evaluation Results (WebNLG+ 2020)
- 2020
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Ingår i: Proceedings of the WebNLG+, 3rd Workshop on Natural Language Generation from the Semantic Web, Dublin 18 December 2020. - Stroudsburg : Association for Computational Linguistics. - 9781952148590
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Konferensbidrag (refereegranskat)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 enables 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.
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| 2. |
- Moussallem, Diego, et al.
(författare)
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A General Benchmarking Framework for Text Generation
- 2020
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Ingår i: Proceedings of the WebNLG+, 3rd Workshop on Natural Language Generation from the Semantic Web, Dublin 18 December 2020. - : Association for Computational Linguistics.
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- The RDF-to-text task has recently gained substantial attention due to the continuous growth of RDF knowledge graphs in number and size. Recent studies have focused on systematically comparing RDF-to-text approaches on benchmarking datasets such as WebNLG. Although some evaluation tools have already been proposed for text generation, none of the existing solutions abides by the Findability, Accessibility, Interoperability, and Reusability (FAIR) principles and involves RDF data for the knowledge extraction task. In this paper, we present BENG, a FAIR benchmarking platform for Natural Language Generation (NLG) and Knowledge Extraction systems with focus on RDF data. BENG builds upon the successful benchmarking platform GERBIL, is open-source and is publicly available along with the data it contains.
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