Question classification based on fine-grained pos annotation of nouns and interrogative pronouns

Question classification is one of the key components of Open Domain Question-Answering System. It has become a research focus for its capability to perform Natural Language Processing. The task of question classification is to assign a class label to each question according to the semantic types of answer. Since the classification precision is affected by the coarse annotation granularity of syntactic features and noises of lexical features, we propose new classification features based on fine-grained PoS annotation of nouns and interrogative pronouns. We firstly refine annotation granularity of syntactic features and then extract the head words with high occurrence frequency and the fine-grained PoS tagging to produce new features so as to reduce the noises of lexical features. A new feature extracting algorithm based on fine-grained PoS annotation is applied to improve the precision of feature extracting. The experimental results demonstrate the effectiveness of the proposed method both in Chinese and English question classification.