A System Description of Natural Language Query over DBpedia
In this paper, the authors describe their system, which is developed as a first step towards implementing a methodology for natural language querying over semantic structured information (semantic web). This paper focuses on interpretation of Natural Language Queries (NL-Queries) to facilitate querying over linked data. This interpretation includes query annotation with linked data concepts (classes and instances), a deep linguistic analysis and semantic similarity/relatedness to generate potential SPARQL queries for a given NL-query. They evaluate their approach on QALD-2 test dataset and achieve a F1 score of 0.46, an average precision of 0.44 and an average recall of 0.48.