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https://hdl.handle.net/10316/115592| Title: | Question Answering over Linked Data with GPT-3 | Authors: | Faria, Bruno Perdigão, Dylan Oliveira, Hugo Gonçalo |
Keywords: | SPARQL Generation; Prompt Engineering; Few-Shot Learning; Question Answering; GPT-3 | Issue Date: | 15-Oct-2023 | Publisher: | Schloss Dagstuhl – Leibniz-Zentrum für Informatik | Project: | C645008882-00000055 | Serial title, monograph or event: | Open Access Series in Informatics (OASIcs) | Volume: | 113 | Place of publication or event: | 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. | URI: | https://hdl.handle.net/10316/115592 | DOI: | 10.4230/OASIcs.SLATE.2023.1 | Rights: | openAccess |
| Appears in Collections: | FCTUC Eng.Informática - Livros e Capítulos de Livros |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| OASIcs.SLATE.2023.1.pdf | 1.63 MB | Adobe PDF | View/Open |
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