A general strategy for researches on Chinese “的(de)” structure based on neural network

Noun phrases reflect people’s understanding of the world entities and play an important role in people’s language system, conceptual system and application system. With the Chinese “的(de)” structure, attributive noun phrases of the combined type can accommodate more words and syntactic structures, resulting in rich levels and complex semantic structures in Chinese sentences. Moreover, the Chinese elliptical “的(de)” structure is also of vital importance to the overall semantic understanding of the sentence. Many researches focus on rule-based models and semantic complement of “verb+的(de)” structure. To tackle these issues, we propose a general three-stage strategy utilizing neural network for the researches on all “的(de)” structure. Experimental results demonstrate that the proposed strategy is effective in boundary definition, elliptical recognition and semantic complement of “的(de)” structure.