DBPEDIA BASED FACTUAL QUESTIONS ANSWERING SYSTEM

The creation of generic natural language query and answering (QA) systems is an active goal of the Semantic Web since it would allow people to conduct any query using their native language. Current solutions already handle factual questions mostly in English. The aim of this work was to develop a QA system to query knowledge bases (KB) such as DBpedia, in a first version, using factual questions in Portuguese, and in a second version, factual questions in English, French and German. This involves representing queries in terms of the KB ontology using SPARQL. The process of constructing a SPARQL query representing the natural language input involves determining: (1) the type of answer that is being sought - a person, a place, etc. - which is done by looking at the wh-words of wh-questions; (2) the main topic of the question - which person, place, etc. - obtained by morphosyntactic analysis to discover the potential subjects of the question; and (3) the properties that can be mapped to the KB ontology for creating a SPARQL query as precise as possible. The first version of the system, working for Portuguese, was tested by with 22 questions without guarantee that the answer was in the KB, and the multilingual version was tested with 30 random questions from QALD 7 (Question Answering over Linked Data) training set. The correctness of the answers was verified as well if the answer exists in the KB when the system did not produced results. A correct answer was produced for 67% of the questions for the Portuguese version and up to 55% (for English) of times for multi-language version considering that the answer existed in the KB. Results show that this approach is promising and further investigation should be done to improve it. The robustness observed, and capability to handle several languages, fosters future work to expand the system to answer questions of other types.