Argumentation-based Inconsistencies Detection for Question-Answering over DBpedia
Elena Cabrio, Julien Cojan, Serena Villata, Fabien L. Gandon, Inria Sophia Antipolis · 2013
Abstract. In the Web of Data, the pieces of information obtained by querying distributed SPARQL endpoints may provide different results for the same query. Moreover, the combination of these query results may lead to an inconsistent set of information about the same topic. In particular, the problem of reconciling information obtained by distributed SPARQL endpoints is encountered in question-answering systems over linked data, where different SPARQL endpoints are queried to retrieve the answer to the user’s question. In this paper, we propose to address this problem by adopting argumentation theory to reason over inconsistent information sets, and provide nevertheless a unique and motivated answer to the user. We implement and evaluate our approach on QAKiS (Question Answering WikiFramework-based system), that exploits multilingual chapters of DBpedia as RDF data sets to be queried using a natural language interface. 1