Improving Chinese Semantic Role Classification with Hierarchical Feature Selection Strategy

In recent years, with the development of Chinese semantically annotated corpus, such as Chinese Proposition Bank and Normalization Bank, the Chinese semantic role labeling (SRL) task has been boosted. Similar to English, the Chinese SRL can be divided into two tasks: semantic role identification (SRI) and classification (SRC). Many features were introduced into these tasks and promising results were achieved. In this paper, we mainly focus on the second task: SRC. After exploiting the linguistic discrepancy between numbered arguments and ARGMs, we built a semantic role classifier based on a hierarchical feature selection strategy. Different from the previous SRC systems, we divided SRC into three sub tasks in sequence and trained models for each sub task. Under the hierarchical architecture, each argument should first be determined whether it is a numbered argument or an ARGM, and then be classified into finegained categories. Finally, we integrated the idea of exploiting argument int...

• Type: Conference
• Year: 2008
• Where: EMNLP
• Authors: Weiwei Ding, Baobao Chang
• Keywords: Chinese Semantic Role, EMNLP 2008, Natural Language Processing, Semantic Role, Semantic Role Identification