  Question processing is a fundamental step in a question answering (QA)
application, and its quality impacts the performance of QA application. The
major challenging issue in processing question is how to extract semantic of
natural language questions (NLQs). A human language is ambiguous. Ambiguity may
occur at two levels; lexical and syntactic. In this paper, we propose a new
approach for resolving lexical ambiguity problem by integrating context
knowledge and concepts knowledge of a domain, into shallow natural language
processing (SNLP) techniques. Concepts knowledge is modeled using ontology,
while context knowledge is obtained from WordNet, and it is determined based on
neighborhood words in a question. The approach will be applied to a university
QA system.
