Speaker
Affilliation
Jadavpur University, India
Abstract
We describe our work on question generation on simple sentences in English, mostly collected from the example sentences in the VerbNet. A named entity recognizer, Part of speech tagger and a chunker have been applied on each of these sentences. The frame and the syntax information for the verb in each sentence are identified using the VerbNet. Verbs can take any of a set of general, adjunct-like arguments. Each verb argument is assigned one (usually unique) thematic role within the class. We associate thematic roles identified for the verb arguments from the VerbNet to the appropriate chunks. Question templates for each primary and secondary frame of a verb class in the VerbNet are stored in a knowledge base. Currently only concept completion questions are being handled. This knowledge base is used to generate appropriate questions from the input sentence. Questions involving named entities in thematic roles assigned to the verb arguments are assigned more importance than other questions. The question generation system is now being expanded to include various verb classes, other question types as well as to handle generating question at the document level.