Hybrid Question Answering Using Heuristic Methods and Linked Data Schema
Rawan Bahmid, Amal Zouaq · 2018
The emergence of linked data in the form of knowledge graphs in RDF has been one of the most recent evolutions of the Semantic Web. This led to the development of natural language question answering systems that automatically translates a question into SPARQL based on these RDF knowledge graphs. In particular, hybrid question answering, the task of question answering by combining both structured (RDF) and unstructured knowledge sources (text) has emerged as an important challenge. This paper tackles hybrid question answering based on natural language questions. We present HAWK_R, a question answering system that improves an open source system called HAWK. We identify its limitations and propose enhancements using heuristic-based methods based on RDF and text search. Our results show a clear improvement of the F-score.