Abstract. This paper describes our system, which is developed as a first step towards implementing a methodology for natural language querying over semantic structured information (semantic web). This work focuses on interpretation of natural language queries (NL-Query) 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. We evaluate our 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
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