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Utilising knowledge graph embeddings for data-to-text generation
(Association for Computational Linguistics, 2020-12-18)
Data-to-text generation has recently seen a move away from modular and pipeline architectures towards end-to-end architectures based on neural networks. In this work, we employ knowledge graph embeddings and explore their ...
NUIG-DSI at the WebNLG+ challenge: Leveraging transfer learning for RDF-to-text generation
(Association for Computational Linguistics, 2020-12-18)
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 ...
NUIG-DSI’s submission to the GEM Benchmark 2021
(Association for Computational Linguistics, 2021-08-05)
This paper describes the submission by NUIG-DSI to the GEM benchmark 2021. We participate in the modeling shared task where we submit outputs on four datasets for data-to-text generation, namely, DART, WebNLG (en), E2E and ...
CURED4NLG: A dataset for table-to-text generation
(University of Galway, 2023)
We introduce CURED4NLG, a dataset for the task of table-to-text generation focusing on the public health domain. The dataset consists of 280 pairs of tables and documents extracted from weekly epidemiological reports ...