Papers by Samuel Reyd
A Copy Mechanism for Handling Knowledge Base Elements in SPARQL Neural Machine Translation (2022.findings-aacl)
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| Challenge: | Current architectures are unable to integrate knowledge base schema and handle questions unseen during training rendering them unusable outside the scope of topics covered in the training set. |
| Approach: | They propose to integrate a copy mechanism for neural SPARQL query generation by adding a knowledge base layer and a dynamic knowledge base vocabulary to two Seq2Seq architectures. |
| Outcome: | The proposed model outperforms existing models on state-of-the-art datasets and shows a significant increase in performance. |