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NUIG-DSI at the WebNLG+ challenge: Leveraging transfer learning for RDF-to-text generation

Pasricha, Nivranshu
; 
Arcan, Mihael
; 
Buitelaar, Paul
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Identifiers
http://hdl.handle.net/10379/16525
 https://doi.org/10.13025/21325
Publication Date
2020-12-18
Keywords
WebNLG, RDF-to-text generation
Type
Workshop paper
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Citation
Pasricha, Nivranshu, Arcan, Mihael, & Buitelaar, Paul. (2020). NUIG-DSI at the WebNLG+ challenge: Leveraging transfer learning for RDF-to-text generation. Paper presented at the 3rd International Workshop on Natural Language Generation from the Semantic Web (WebNLG+) Virtual, Dublin, Ireland, 18 December.
Abstract
This paper describes the system submitted by NUIG-DSI to the WebNLG+ challenge 2020 in the RDF-to-text generation task for the English language. For this challenge, we leverage transfer learning by adopting the T5 model architecture for our submission and fine-tune the model on the WebNLG+ corpus. Our submission ranks among the top five systems for most of the automatic evaluation metrics achieving a BLEU score of 51.74 over all categories with scores of 58.23 and 45.57 across seen and unseen categories respectively.
Funder
Science Foundation Ireland
European Regional Development Fund
Publisher
Association for Computational Linguistics
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Rights
Attribution-NonCommercial-NoDerivs 3.0 Ireland
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Data Science Institute (Workshop Papers)