Recent trends in Question Answering (QA) have led to numerous studies focusing on pre-senting answers in a form which closely re-sembles a human generated answer. These studies have used a range of techniques which use the structure of knowledge, generic lin-guistic structures and template based ap-proaches to construct answers as close as pos-sible to a human generate answer, referred to as human competitive answers. This paper re-ports the results of an empirical study which uses the linguistic structure of the source ques-tion as the basis for a human competitive answer. We propose a typed dependency based approach to generate an answer sen-tence where linguistic structure of the ques-tion is transformed and realized into a sen-tence containing the answer. We employ the factoid questions from QALD-2 training ques-tion set to extract typed dependency patterns based on the root of the parse tree. Using iden-tified patterns we generate a rule set which is used to generate a natural language sentence containing the answer extracted from a knowl-edge source, realized into a linguistically cor-rect sentence. The evaluation of the approach is performed using QALD-2 testing factoid questions sets with a 78.84 % accuracy. The top-10 patterns extracted from training dataset were able to cover 69.19 % of test questions.
