Automatic Question Generation based on Sentence Structure Analysis

Automated question generation is a key problem in computational linguistics and knowledge engineering. There are different approaches and methodologies like template-based, syntax-based, or machine learning approaches. The paper investigates the efficiency and analysis of the role of the embedding module in sentence parsing. Embedding language models are important modules and the performed tests show that embeddings can provide a high accuracy in semantic-level similarity methods.