onIQ: An Ontology-Independent Natural Language Interface for Building SPARQL Queries
Ilie Cristian Dorobăț, Vlad Posea · 2020
Publishing data in Linked Data tends to capture more and more space because this way of representation of data allows linking the data, which leads to an increase in the degree of representation and, why not, the quality of data. Unfortunately, Linked Data has a much more complex and heterogeneous structure than other ways of data representation, which means only a larger learning curve of SPARQL, the triplestore query language. In this paper, we propose a framework, Ontology-Independent Natural Language Query Interface for Building SPARQL Queries, for translating queries formulated in natural language into SPARQL queries, so as to facilitate the adoption of Linked Data. The framework uses spaCy library for applying specific NLP techniques for syntactic analysis and extraction of the elements needed to build the SPARQL query. Through WordNet, the synonyms for the words extracted from the user question are identified, and then, in order to map them with properties from the used ontologies, the degree of similarity is calculated. Finally, the SPARQL query is built and the user can use it for querying the triplestore.