Implicit relation-based question answering to answer simple questions over DBpedia

Authors: MARYAM JAMEHSHOURANI, AFSANEH FATEMI, MOHAMMADALI NEMATBAKHSH

Abstract: RDF-based question answering systems give users the capability of natural language querying over RDF data. In order to respond to natural language questions, it is necessary that the main concept of the question be interpreted correctly, and then it is mapped to RDF data. A natural language question includes entities, classes, and implicit and explicit relationships. In this article, by focusing on identification and mapping of implicit relationships in the question (in addition to the explicit relationships), the mapping step has been improved. In the proposed solution (IRQA), entities and implicit/explicit relationships are identified by means of the provided rules and then will be presented as a graph. In the next phase, according to the determined priority of graph nodes, unknown nodes and their adjacent relationships are mapped to their peers in the RDF dataset. The proposed solution is evaluated on the QALD-3 test set. The results prove that the proposed work has improved performance in mapping implicit relationships and reveals higher precision and F-measure values.

Keywords: Semantic web, question answering, linked data, natural language, SPARQL, RDF

Full Text: PDF