Towards Verbalizing SPARQL Queries in Arabic

Abstract

With the wide spread of Open Linked Data and Semantic Web technologies, a larger amount of data has been published on the Web in the RDF and OWL formats. This data can be queried using SPARQL, the Semantic Web Query Language. SPARQL cannot be understood by ordinary users and is not directly accessible to humans, and thus they will not be able to check whether the retrieved answers truly correspond to the intended information need. Driven by this challenge, natural language generation from SPARQL data has recently attracted a considerable attention. However, most existing solutions to verbalize SPARQL in natural language focused on English and Latin-based languages. Little effort has been made on the Arabic language which has different characteristics and morphology. This work aims to particularly help Arab users to perceive SPARQL queries on the Semantic Web by translating SPARQL to Arabic. It proposes an approach that gets a SPARQL query as an input and generates a query expressed in Arabic as an output. The translation process combines both morpho-syntactic analysis and language dependencies to generate a legible and understandable Arabic query. The approach was preliminary assessed with a sample query set, and results indicated that 75% of the queries were correctly translated into Arabic.