Automatic Generation of Semantic Dependency Rules for Japanese Noun Phrases with Particles "no"

The most important problems of dependency analysis are separated into three kinds of dependencies: noun to verb dependency, verb to verb dependency and noun to noun dependency. Recently, efficient methods have been developed for the first two problems. However, the third problem, namely noun phrase analysis, has not yet been solved. One of the most typical and important noun phrases in the Japanese language is the expression “A B C” (similar to “A of B of C” in English), which is composed of three nouns, A, B and C. In order to analyze this type of noun phrase, this paper proposes a method to generate dependency rules automatically. In this method, semantic structures of noun phrases are defined using a semantic attribute system which has recently been developed by NTT Japan. 4 kinds of semantic dependency rules, one-dimensional, two-dimensional, three-dimensional rules and exceptional rules were generated in the order of generality using examples extracted from the corpus. In the experiments, this method was applied to 10,000 Japanese noun phrases; 198 rules, 1,480 rules, 136 rules and 0 rules, respectively, were generated for each of the above 4 rule groups. The generated rules were applied to the dependency analysis, resulting in an accuracy rate of 85.8%.