Knowledge Based Question Answering (KBQA) is concerned with the possibility of querying data by posing questions in Natural Language (NL), that is by far, the most (human) common form of expressing an information need. This work reviews an approach to Question Answering that has the goal to transform Natural Language questions into SPARQL queries over cultural heritage knowledge bases. The key idea is to apply a rule-based classification process that we call template matching and that we have implemented in a prototype using logic programming. In the paper we discuss about the application of the prototype in real use-case, and indicate ongoing and future directions of work.
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|Titolo:||Querying cultural heritage knowledge bases in natural language: Discussion paper|
|Data di pubblicazione:||2019|
|Appare nelle tipologie:||4.1 Contributo in Atti di convegno|