Method and system for automatic treebank transformation based on pattern embedding

Abstract

The invention relates to an automatic tree bank conversion method and system based on pattern embedding, which is designed to obtain an accurate supervised conversion model. The present invention is based on the automatic tree bank conversion method of pattern embedding, and determines the word w i and the word w j pattern; the word w i and the word w j The pattern of is transformed into the corresponding pattern embedding vector; the word w in the source tree i , word w j , the smallest common ancestor node w a The dependency labels corresponding to the three are respectively transformed into dependency embedding vectors; the pattern embedding vector and the three dependency embedding vectors are spliced ​​together as the word w in the source tree i and the word w j The representation vector of the structural information of the cyclic neural network, the top-level output of the recurrent neural network is spliced ​​with the representation vector respectively, and used as the input of the perceptron MLP; the word w is obtained by biaffine calculation i and the word w j The target end depends on the arc-score value; the invention makes full use of the source-end syntax tree to describe the corresponding laws of the two labeling specifications, and finally completes the high-quality tree bank conversion.

Description

technical field [0001] The invention belongs to the technical field of natural language processing, and in particular relates to an automatic tree bank conversion method and system based on pattern embedding. Background technique [0002] At present, researchers have carried out a lot of research and development work in tree bank research, and have also achieved considerable results. The annotation systems used by these treebanks are very different, and they can be roughly divided into two types according to the description method, one is the phrase structure tree, and the other is the dependency tree. [0003] For the dependency tree, the dependency annotations of the two treebanks follow different annotation specifications, and the two treebanks are said to be heterogeneous. Many mainstream languages ​​in the world have multiple large-scale heterogeneous treebanks. Since the construction of treebanks requires a very high labor cost, how to use different heterogeneous tree...

AI Technical Summary

Problems solved by technology

The main problem of the indirect method is that the source-end treebank is not fully utilized, and it cannot effectively describe the corresponding rules between norms; while the direct method based on transformation is limited by the lack of double-tree alignment data, and cannot effectively learn the relationship between norms. Corresponding law, so the conversion effect is average

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