Abstract
A new method is proposed for constructing the Chinese sentential semantic structure in this paper. The method adopts the features including predicates, relations between predicates and basic arguments, relations between words, and case types to train the models of CRF++ and dependency parser. On the basis of the data set in Beijing Forest Studio-Chinese Tagged Corpus (BFS-CTC), the proposed method obtains precision value of 73.63% in open test. This result shows that the formalized computer processing can construct the sentential semantic structure absolutely. The features of predicates, topic and comment extracted with the method can be applied in Chinese information processing directly for promoting the development of Chinese semantic analysis. The method makes the analysis of sentential semantic analysis based on large scale of data possible. It is a tool for expanding the corpus and has certain theoretical research and practical application value.
| Original language | English |
|---|---|
| Pages (from-to) | 110-117 |
| Number of pages | 8 |
| Journal | Journal of Beijing Institute of Technology (English Edition) |
| Volume | 24 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - 1 Mar 2015 |
Keywords
- Chinese sentential semantic model
- Conditional random field
- Dependency parse
- Sentential semantic structure