Question answering (QA) is the study on the methodology that returns exact answers to natural language questions. This paper attempts to increase the coverage and accuracy of QA systems by narrowing the semantics gap between questions with terms written in abbreviations and their potential answers. To achieve this objective, the processing includes (1) identifying terms that might be abbreviations from the user's natural language question; (2) retrieving documents relevant to that abbreviation term; (3) filtering noun phrases that are considered to be potential long forms for that abbreviation within the returned result.