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Now showing items 41-47 of 47
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 ...
Enhancing multiple-choice question answering with causal knowledge
(Association for Computational Linguistics, 2021-06-10)
The task of causal question answering aims to reason about causes and effects over a provided real or hypothetical premise. Recent approaches have converged on using transformer-based language models to solve question ...
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 ...
Intent classification by the use of automatically generated knowledge graphs
(MDPI, 2023-05-12)
Intent classification is an essential task for goal-oriented dialogue systems for automatically identifying customers¿ goals. Although intent classification performs well in general settings, domain-specific user goals can ...
Towards bootstrapping a chatbot on industrial heritage through term and relation extraction
(Association for Computational Linguistics (ACL), 2022-11-20)
We describe initial work in developing a
methodology for the automatic generation of a
conversational agent or ‘chatbot’ through term
and relation extraction from a relevant corpus
of language data. We develop our ...
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 ...