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DOI: 10.4230/OASIcs.SLATE.2023.1

Question Answering over Linked Data with GPT-3

Authors: Bruno Faria, Dylan Perdigão, and Hugo Gonçalo Oliveira

Published in: OASIcs, Volume 113, 12th Symposium on Languages, Applications and Technologies (SLATE 2023)

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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Bruno Faria, Dylan Perdigão, and Hugo Gonçalo Oliveira. Question Answering over Linked Data with GPT-3. In 12th Symposium on Languages, Applications and Technologies (SLATE 2023). Open Access Series in Informatics (OASIcs), Volume 113, pp. 1:1-1:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@InProceedings{faria_et_al:OASIcs.SLATE.2023.1,
  author =	{Faria, Bruno and Perdig\~{a}o, Dylan and Gon\c{c}alo Oliveira, Hugo},
  title =	{{Question Answering over Linked Data with GPT-3}},
  booktitle =	{12th Symposium on Languages, Applications and Technologies (SLATE 2023)},
  pages =	{1:1--1:15},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-291-4},
  ISSN =	{2190-6807},
  year =	{2023},
  volume =	{113},
  editor =	{Sim\~{o}es, Alberto and Ber\'{o}n, Mario Marcelo and Portela, Filipe},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.SLATE.2023.1},
  URN =		{urn:nbn:de:0030-drops-185155},
  doi =		{10.4230/OASIcs.SLATE.2023.1},
  annote =	{Keywords: SPARQL Generation, Prompt Engineering, Few-Shot Learning, Question Answering, GPT-3}
}

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Question Answering over Linked Data with GPT-3

Abstract

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