Translating Natural Language Questions into CIDOC-CRM SPARQL Queries to Access Cultural Heritage Knowledge Bases

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F26%3AH4NL75SU" target="_blank" >RIV/00216208:11320/26:H4NL75SU - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1145/3715156" target="_blank" >http://dx.doi.org/10.1145/3715156</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1145/3715156" target="_blank" >10.1145/3715156</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Translating Natural Language Questions into CIDOC-CRM SPARQL Queries to Access Cultural Heritage Knowledge Bases

Popis výsledku v původním jazyce

To explore information on the semantic web, SPARQL queries or DL-queries are suitable tools. However, users interested in exploring the content of such knowledge bases often find it challenging to employ formal query languages, as this requires familiarity with the target domain's representation model. To address these challenges, a question-answering system that automatically translates natural language questions into SPARQL queries, over the Smithsonian American Art Museum CIDOC-CRM representation is presented. The proposed approach uses an ontology, named Query Ontology, defined to represent the natural language concepts and relations specific to the question's domain. This system's architecture uses a traditional natural language processing symbolic approach, with a pipeline of modules for the syntactic, semantic, and pragmatic analysis. An evaluation of the proposed system is presented and shows very promising results. © 2025 Copyright held by the owner/author(s).

Název v anglickém jazyce

Translating Natural Language Questions into CIDOC-CRM SPARQL Queries to Access Cultural Heritage Knowledge Bases

Popis výsledku anglicky

To explore information on the semantic web, SPARQL queries or DL-queries are suitable tools. However, users interested in exploring the content of such knowledge bases often find it challenging to employ formal query languages, as this requires familiarity with the target domain's representation model. To address these challenges, a question-answering system that automatically translates natural language questions into SPARQL queries, over the Smithsonian American Art Museum CIDOC-CRM representation is presented. The proposed approach uses an ontology, named Query Ontology, defined to represent the natural language concepts and relations specific to the question's domain. This system's architecture uses a traditional natural language processing symbolic approach, with a pipeline of modules for the syntactic, semantic, and pragmatic analysis. An evaluation of the proposed system is presented and shows very promising results. © 2025 Copyright held by the owner/author(s).

Druh

J_SC - Článek v periodiku v databázi SCOPUS

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

—

Návaznosti

—

Rok uplatnění

2025

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Journal on Computing and Cultural Heritage

ISSN

1556-4673

e-ISSN

—

Svazek periodika

18

Číslo periodika v rámci svazku

2

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

13

Strana od-do

21

Kód UT WoS článku

—

EID výsledku v databázi Scopus

2-s2.0-105009650128