面向医药领域的中文语义解析

Semantic parsing is the task of transforming natural-language sentences into complete, formal, symbolic meaning representations (MR) suitable for reasoning or machine-understanding. In recent years, the research of semantic parsing in English has made great progress. However, little work has been done in Chinese semantic parsing. The medical field has a rich source of data, which is delivered by text. It is difficult for computer to process and understand the medical data.In this paper, we propose a statistical approach called CSPMF(Chinese Semantic Parsing for Medicine Field)aiming at Chinese semantic parsing for medicine text, which consider the process of converting Chinese sentence into its corresponding meaning as a machine translation procedure. At first, we create a new dataset of medicine for Chinese Semantic Parsing, in which each data contains a Chinese sentence and its accurate meaning. Then we use the word alignment model to acquire the bilingual dictionary made up by the Chinese natural language string and its meaning. In the end, we determine the ultimate semantic analysis by learning a statistical model. Experiments show that CSPMF performs well with higher precision and recall.