This paper explores the possibility of pre-senting additional contextual information as a method of answer presentation Question An-swering. In particular the paper discusses the result of employing Bag of Words (BoW) and Bag of Concepts (BoC) models to retrieve contextual information from a Linked Data resource, DBpedia. DBpedia provides struc-tured information on wide variety of entities in the form of triples. We utilize the QALD question sets consisting of a 100 instances in the training set and another 100 in the testing set. The questions are categorized into single entity and multiple entity questions based on the number of entities mentioned in the ques-tion. The results show that both BoW (syn-tactic models) and BoC (semantic models) are not capable enough to select contextual infor-mation for answer presentation. The results further reveals that pragmatic aspects, in par-ticular, pragmatic intent and pragmatic infer-ence play a crucial role in contextual informa-tion selection in the answer presentation.
