Extracting RDF triples using the Stanford Parser
One of the most important tasks in Natural Language Processing (NLP) theory consists of simplifying sentences in order to extract their structure and the most relevant information they contain. This paper presents a method to obtain RDF triples (subject predicate object) from questions using the Stanford Parser. Our approach is mainly based on a careful analysis of the dependency tree produced by the Stanford Parser. We will also make use of some extra tools (named entity recognizer, part ofspeech tagger, etc) Our algorithms have been implemented and are part of a query answering tool1.