Accessing Semistructured Data with KGs and LLMs

S Karkee; E Botoeva; S Coombes; A Jordanous; Ö Kafali; Davide Lanti

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Accessing Semistructured Data with KGs and LLMs

Conference proceeding

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Accessing Semistructured Data with KGs and LLMs

S Karkee, E Botoeva, S Coombes, A Jordanous, Ö Kafali and Davide Lanti

Proceedings of the 38th International Workshop on Description Logics (DL 2025), Vol.4091, pp.1-11

CEUR Workshop Proceedings, 4091

International Workshop on Description Logics (Opole, 03/09/2025–06/09/2025)

2025

Handle:

https://hdl.handle.net/10863/52425

Abstract

Semi-structured data

Large Language Models (LLMs)

Ontology-based data access

RML

We demonstrate a principled way to query semistructured data by integrating natural language processing capabilities into knowledge graph generation. We instantiate RML mappings with LLM queries to extract ontological terms from plain text. We evaluate our approach on pharmaceutical data in JSON format.

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Details

Title: Accessing Semistructured Data with KGs and LLMs
Creators: S Karkee
E Botoeva
S Coombes
A Jordanous
Ö Kafali
Davide Lanti
Publication Details: Proceedings of the 38th International Workshop on Description Logics (DL 2025), Vol.4091, pp.1-11
Editor(s): Tendera L, Ibáñez-García Y, Koopmann P
ISSN: 1613-0073
Conference: International Workshop on Description Logics (Opole, 03/09/2025–06/09/2025)
Series / Volume: CEUR Workshop Proceedings
4091
Publisher: CEUR-WS
Number of pages: 11
Identifiers: (UNIBZ)98396211
991007355764601241
Scopus ID: n.a.
Copyright: Open Access: under Creative Commons License Attribution 4.0 International (CC BY 4.0).
Academic Unit: Faculty of Engineering
Language: English
Resource Type: Conference proceeding
Author Names String: Karkee S, Botoeva E, Coombes S, Jordanous A, Kafali Ö, Lanti D
Additional Description: Editors/Supervisors: Tendera L, Ibáñez-García Y, Koopmann P

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