Exploring linguistically-rich patterns for question generation

Linguistic patterns reflect the regularities of Natural Language and their applicability is acknowledged in several Natural Language Processing tasks. Particularly, in the task of Question Generation, many systems depend on patterns to generate questions from text. The approach we follow relies on patterns that convey lexical, syntactic and semantic information, automatically learned from largescale corpora. In this paper we discuss the impact of varying several parameters during pattern learning and matching in the Question Generation task. In particular, we introduce semantics (by means of named entities) in our lexico-syntactic patterns. We evaluate and compare the number and quality of the learned patterns and the matched text segments. Also, we detail the influence of the patterns in the generation of natural language questions.