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Bridging NLP and semantic web to enhance user interactions with the web of data
As the social web is spreading among people and the web of data continues to grow (e.g. Linked Data initiatives), there is an increasing need to allow easy interactions between non-expert users and data available on the Web. In this perspective, we address the development of methods for a flexible mapping between natural language expressions, and concepts and relations in structured knowledge bases. In the first part of this talk, I will present QAKiS (i.e. Question Answering wiKiframework-based System), that allows end users to submit a query to an RDF triple store in English and obtain the answer in the same language, hiding the complexity of the non intuitive formal query languages involved in the resolution process. At the same time, the expressiveness of these standards is exploited to scale to the huge amounts of available semantic data. In its current implementation, QAKiS addresses the task of QA over structured Knowledge Bases (e.g. multilingual chapters of DBpedia) where the relevant information is expressed also in unstructured form (e.g. Wikipedia pages). Its major novelty is to implement a relation-based match for question interpretation, to convert the user question into a query language (e.g. SPARQL). In the second part of the talk, I will briefly outline another research line I am currently investigating, i.e. the combination of natural language processing techniques to semantic inferences and argumentation theory to support online debates interactions.