Question systematization using templates

摘要

Question is a crucial construct of natural language. Systematic, error free question is a basic need of different applications of natural language. Many research works have been focused on `statement' formation but the issue of `systematic question' formation is less focused. This research work resolves above issue through systematization process using Template based approach which is accompanied by Dictionary approach and powerful NLP technique like Maximum Entropy based POS Tagging technique. Systematization process aims to reform proper flawless question from the erroneous input question by removing existing errors present in order of words, word spelling and removing ambiguous synonyms of the words. This work deals with domain specific WH-questions of English language. Additionally it also works on imperative questions. Template based approach is supported with a key concept of `Question Templates' which are designed with human intelligence keeping detail knowledge of various lingual constructs, their grammar and domain specific questionnaire. This work is useful in various fields, for example in academics to set question papers, to assist English learners, to produce intermediate output for complex systems like question-answering system to retrieve correct answer from a huge dataset.