Automated Question Generation tool for structured data

For competitive examinations (e.g. GMAT, CAT) and for various offline and online academic courses, test questions need to be written by human authors. These question-writing tasks take significant manual effort and time. To simplify this effort, we propose an Automatic Question Generation system that focuses on questions that can be generated in English from structured data. This paper explains an approach, which takes a data table as input and generates questions of varying types. The data is preprocessed and categorized according to their class (numeric and nonnumeric). Appropriate templates are used to create various kinds of questions. A custom tagger is built, which takes the data entry and assigns it an entity, such that it can be generalized to a particular entity name. For uncategorized or unrecognized entities, options to add or modify entities are also provided. Preliminary experimental work carried out using this template system shows promising results. To the best of our knowledge, this is the first such question generation system based on structured data in the form of tables.