{"_id":"55073","publisher":"Association for Computational Linguistics","language":[{"iso":"eng"}],"main_file_link":[{"url":"https://aclanthology.org/2020.webnlg-1.3.pdf"}],"page":"27-33","user_id":"14972","author":[{"full_name":"Moussalem, Diego","last_name":"Moussalem","first_name":"Diego"},{"last_name":"Kaur","first_name":"Paramjot","full_name":"Kaur, Paramjot"},{"last_name":"Castro-Ferreira","first_name":"Thiago","full_name":"Castro-Ferreira, Thiago"},{"full_name":"van der Lee, Chris","first_name":"Chris","last_name":"van der Lee"},{"first_name":"Conrads Felix","last_name":"Shimorina","full_name":"Shimorina, Conrads Felix"},{"last_name":"Conrads","first_name":"Felix","full_name":"Conrads, Felix"},{"first_name":"René","last_name":"Speck","full_name":"Speck, René"},{"last_name":"Gardent","first_name":"Claire","full_name":"Gardent, Claire"},{"last_name":"Mille","first_name":"Simon","full_name":"Mille, Simon"},{"full_name":"Ilinykh, Nikolai","first_name":"Nikolai","last_name":"Ilinykh"},{"first_name":"Axel-Cyrille","last_name":"Ngonga Ngomo","full_name":"Ngonga Ngomo, Axel-Cyrille"}],"status":"public","title":"A general benchmarking framework for text generation","year":"2020","date_updated":"2026-10-15T11:47:02Z","date_created":"2024-07-04T11:59:39Z","place":"Dublin, Ireland","type":"conference","citation":{"mla":"Moussalem, Diego, et al. “A General Benchmarking Framework for Text Generation.” <i>Proceedings of the 3rd WebNLG Workshop on Natural Language Generation from the Semantic Web (WebNLG+)</i>, Association for Computational Linguistics, 2020, pp. 27–33.","bibtex":"@inproceedings{Moussalem_Kaur_Castro-Ferreira_van der Lee_Shimorina_Conrads_Speck_Gardent_Mille_Ilinykh_et al._2020, place={Dublin, Ireland}, title={A general benchmarking framework for text generation}, booktitle={Proceedings of the 3rd WebNLG Workshop on Natural Language Generation from the Semantic Web (WebNLG+)}, publisher={Association for Computational Linguistics}, author={Moussalem, Diego and Kaur, Paramjot and Castro-Ferreira, Thiago and van der Lee, Chris and Shimorina, Conrads Felix and Conrads, Felix and Speck, René and Gardent, Claire and Mille, Simon and Ilinykh, Nikolai and et al.}, year={2020}, pages={27–33} }","ama":"Moussalem D, Kaur P, Castro-Ferreira T, et al. A general benchmarking framework for text generation. In: <i>Proceedings of the 3rd WebNLG Workshop on Natural Language Generation from the Semantic Web (WebNLG+)</i>. Association for Computational Linguistics; 2020:27-33.","ieee":"D. Moussalem <i>et al.</i>, “A general benchmarking framework for text generation,” in <i>Proceedings of the 3rd WebNLG Workshop on Natural Language Generation from the Semantic Web (WebNLG+)</i>, 2020, pp. 27–33.","apa":"Moussalem, D., Kaur, P., Castro-Ferreira, T., van der Lee, C., Shimorina, C. F., Conrads, F., Speck, R., Gardent, C., Mille, S., Ilinykh, N., &#38; Ngonga Ngomo, A.-C. (2020). A general benchmarking framework for text generation. <i>Proceedings of the 3rd WebNLG Workshop on Natural Language Generation from the Semantic Web (WebNLG+)</i>, 27–33.","chicago":"Moussalem, Diego, Paramjot Kaur, Thiago Castro-Ferreira, Chris van der Lee, Conrads Felix Shimorina, Felix Conrads, René Speck, et al. “A General Benchmarking Framework for Text Generation.” In <i>Proceedings of the 3rd WebNLG Workshop on Natural Language Generation from the Semantic Web (WebNLG+)</i>, 27–33. Dublin, Ireland: Association for Computational Linguistics, 2020.","short":"D. Moussalem, P. Kaur, T. Castro-Ferreira, C. van der Lee, C.F. Shimorina, F. Conrads, R. Speck, C. Gardent, S. Mille, N. Ilinykh, A.-C. Ngonga Ngomo, in: Proceedings of the 3rd WebNLG Workshop on Natural Language Generation from the Semantic Web (WebNLG+), Association for Computational Linguistics, Dublin, Ireland, 2020, pp. 27–33."},"publication":"Proceedings of the 3rd WebNLG Workshop on Natural Language Generation from the Semantic Web (WebNLG+)","abstract":[{"lang":"eng","text":"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 opensource and is publicly available along with the data it contains."}]}