ISOFT at QALD-4: Semantic Similarity-based Question Answering System over Linked Data.
Seonyeong Park, Hyosup Shim, Gary Geunbae Lee · CLEF (Working Notes) · 2014
We present a question answering system over linked data. We use natural language processing tools to extract slots and SPARQL templates from the question. Then, we use semantic similarity to map a natural language question to a SPARQL query. We combine important words to avoid loss of meaning, and compare combined words with uniform resource identifiers (URIs) from a knowledgebase (KB). This process is more powerful than comparing each word individually. Using our method, the problem of mapping a phrase of a user question to URIs from a KB can be more easily solved than without our method; this method improves the F-measure of the system.