Testing ChatGPT-aided SparQL generation for semantic construction information retrieval

Yuan Zheng, Olli Seppänen, Sebastian Seiss, Jürgen Melzner

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

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Abstract

Recently there has been a strong interest in using semantic technologies to improve information management in the construction domain. Ontologies provide a formalized domain knowledge representation that provides a structured information model to facilitate information management issues such as formalization and integration of construction workflow information and data and enables further applications such as information retrieval and reasoning. SPARQL Protocol And RDF Query Language (SPARQL) queries are the main approaches to conduct the information retrieval from the Resource Description Framework (RDF) format data. However, there is a barrier for end users to develop the SPARQL queries, as it requires proficient skills to code them. This challenge hinders the practical application of ontology-based approaches on construction sites. As a generative language model, ChatGPT has already illustrated its capability to process and generate human-like text, including the capability to generate the SPARQL for domain-specific tasks. However, there are no specific tests evaluating and assessing the SPARQL-generating capability of ChatGPT within the construction domain. Therefore, this paper focuses on exploring the usage of ChatGPT with a case of importing the Digital Construction Ontologies (DiCon) and generating SPARQL queries for specific construction workflow information retrieval. We evaluate the generated queries with metrics including syntactical correctness, plausible query structure, and coverage of correct answers
Original languageEnglish
Title of host publicationCONVR 2023 - Proceedings of the 23rd International Conference on Construction Applications of Virtual Reality
Subtitle of host publicationManaging the Digital Transformation of Construction Industry
EditorsPietro Capone, Vito Getuli, Farzad Pour Rahimian, Nashwan Dawood, Alessandro Bruttini, Tommaso Sorbi
PublisherFirenze University Press
Pages751-760
Number of pages10
ISBN (Electronic)979-12-215-0289-3, 979-12-215-0257-2
DOIs
Publication statusPublished - 2023
MoE publication typeA4 Conference publication
EventInternational Conference on Construction Applications of Virtual Reality - Firenze, Italy
Duration: 13 Nov 202315 Nov 2023
Conference number: 23

Publication series

NameProceedings e report
Number137
ISSN (Print)2704-601X
ISSN (Electronic)2704-5846

Conference

ConferenceInternational Conference on Construction Applications of Virtual Reality
Abbreviated titleCONVR
Country/TerritoryItaly
CityFirenze
Period13/11/202315/11/2023

Keywords

  • semantic web
  • ontology
  • ChatGPT
  • RDF
  • information retrieval
  • construction

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