In this paper we tackle question analysis in the medical domain. More precisely, we study how to translate a natural language question into a machine-readable representation. The underlying transformation process requires determining three key points: (i) What are the main characteristics of medical questions? (ii) Which methods are the most suited to extract these characteristics? and (iii) how to translate the extracted information into a machine- readable representation? We present a complete question analysis approach including medical entity recognition, relation extraction and automatic translation to SPARQL queries. Our study supports the claim that SPARQL can represent a wide range of natural language questions.
['Asma Ben Abacha', 'Pierre Zweigenbaum']
Analyse et transformation des questions médicales en requêtes SPARQL