A Chinese-English patent machine translation system based on the theory of hierarchical network of concepts

Compared with ordinary text, patent text often has more complex sentence structure and more ambiguity of multiple verbs. To deal with these problems, this paper presents a rule-based Chinese-English patent machine translation (MT) system based on the theory of hierarchical network of concepts (HNC). In this system, the whole procedure are divided into three main parts, the semantic analysis of the source language, the transitional transformation from the source language to the target language and the generation of the target language. The knowledge base and the rule set are obtained from manually analyzing the semantic features of a training set which contains more than 6 000 Chinese patent sentences, and a specific method of evaluation is provided during the experiment.