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Question Answering over Linked Data with GPT-3

2023-08-15Symposium on Languages, Applications and Technologies 2023Code Available0· sign in to hype

Bruno Faria, Dylan Perdigão, Hugo Gonçalo Oliveira

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Abstract

This paper explores GPT-3 for answering natural language questions over Linked Data. Different engines of the model and different approaches are adopted for answering questions in the QALD-9 dataset, namely: zero and few-shot SPARQL generation, as well as fine-tuning in the training portion of the dataset. Answers retrieved by the generated queries and answers generated directly by the model are also compared. Overall results are generally poor, but several insights are provided on using GPT-3 for the proposed task.

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