Using Linguistic Analysis to Translate Arabic Natural Language Queries to SPARQL

TL;DR

This paper introduces a linguistic analysis-based method to translate Arabic natural language queries into SPARQL, enabling querying Arabic content on the Semantic Web without relying on English NLP tools.

Contribution

It presents a domain-independent approach leveraging Arabic linguistic analysis and ontology matching to generate SPARQL queries from Arabic NL questions.

Findings

Successfully translated Arabic NL queries to SPARQL

Supported advanced semantic features like negation and conjunctions

Confirmed feasibility through evaluation with datasets

Abstract

The logic-based machine-understandable framework of the Semantic Web often challenges naive users when they try to query ontology-based knowledge bases. Existing research efforts have approached this problem by introducing Natural Language (NL) interfaces to ontologies. These NL interfaces have the ability to construct SPARQL queries based on NL user queries. However, most efforts were restricted to queries expressed in English, and they often benefited from the advancement of English NLP tools. However, little research has been done to support querying the Arabic content on the Semantic Web by using NL queries. This paper presents a domain-independent approach to translate Arabic NL queries to SPARQL by leveraging linguistic analysis. Based on a special consideration on Noun Phrases (NPs), our approach uses a language parser to extract NPs and the relations from Arabic parse trees and match them to the underlying ontology. It then utilizes knowledge in the ontology to group NPs into triple-based representations. A SPARQL query is finally generated by extracting targets and modifiers, and interpreting them into SPARQL. The interpretation of advanced semantic features including negation, conjunctive and disjunctive modifiers is also supported. The approach was evaluated by using two datasets consisting of OWL test data and queries, and the obtained results have confirmed its feasibility to translate Arabic NL queries to SPARQL.