Semantic Labeling of Chinese Serial Verb Sentences Based on Feature Structure

Parsing Chinese serial verb sentences is a key issue in NLP. Many controversies arise from serial verb sentences. This paper puts forward a novel model “the Feature Structure theory” to resolve the semantic labeling of Chinese serial verb sentences. We analyze the difficulties in annotating these sentences, and compare Feature Structure with traditional dependency structure. Feature Structure represents more semantic information and more semantic relations. Feature Graph is a recursive undirected graph, allows nesting and multiple correlations.