The paper presents an Italian question answering system over linked data. We use a model-based approach to question answering based on an ontology lexicon in lemon format. The system exploits an automatically generated lexicalized grammar that can then be used to interpret and transform questions into SPARQL queries. We apply the approach for the Italian language and implement a question answering system that can answer more than 1.6 million questions over the DBpedia knowledge graph.

An Italian Question Answering System Based on Grammars Automatically Generated from Ontology Lexica

Gennaro Nolano
;
Maria Pia di Buono;
2021-01-01

Abstract

The paper presents an Italian question answering system over linked data. We use a model-based approach to question answering based on an ontology lexicon in lemon format. The system exploits an automatically generated lexicalized grammar that can then be used to interpret and transform questions into SPARQL queries. We apply the approach for the Italian language and implement a question answering system that can answer more than 1.6 million questions over the DBpedia knowledge graph.
2021
Inglese
Elisabetta Fersini, Marco Passarotti, Viviana Patti
CLiC-it 2021 - Proceedings of the Eighth Italian Conference on Computational Linguistics
contributo
CLiC-it 2021 Italian Conference on Computational Linguistics 2021
6
9791280136947
AILC - Associazione Italiana di Linguistica Computazionale
Trento
ITALIA
Esperti anonimi
January 26-28, 2022
Milan, Italy
Internazionale
5
Nolano, Gennaro; Fazleh Elahi, Mohammad; di Buono, Maria Pia; Ell, Basil; Cimiano, Philipp
restricted
273
info:eu-repo/semantics/conferenceObject
4 Contributo in Atti di Convegno (Proceeding)::4.1 Contributo in Atti di convegno
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11574/202005
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