{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/question-answering-over-linked-data-with-gpt","title":"Question Answering over Linked Data with GPT-3","arxiv_id":null,"date":"2023-08-15","proceeding":"Symposium on Languages, Applications and Technologies 2023 8","authors":["Bruno Faria","Dylan Perdigão","Hugo Gonçalo Oliveira"],"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.","url_abs":"https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.SLATE.2023.1","url_pdf":"https://drops.dagstuhl.de/storage/01oasics/oasics-vol113-slate2023/OASIcs.SLATE.2023.1/OASIcs.SLATE.2023.1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"question-answering-over-linked-data-with-gpt","repo_url":"https://github.com/brunofaria1322/GPT3-over-QALD9","is_official":0,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"knowledge-base-question-answering","task_name":"Knowledge Base Question Answering"},{"task_slug":"question-answering","task_name":"Question Answering"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}