Disambiguation-free unsupervised part-of-speech tagging method based on error-correcting output codes

Abstract

The invention discloses a disambiguation-free unsupervised part-of-speech tagging method based on error-correcting output codes. The disambiguation-free unsupervised part-of-speech tagging method comprises two main steps: (1) on the basis of a part-of-speech directory, generating training data; and (2) on the basis of the error-correcting output codes, carrying out training and testing. The disambiguation-free unsupervised part-of-speech tagging method does not need to tag corpora, can be applied to a part-of-speech tagging problem of a language which can not easily obtain the tagged corpus, and does not need to carry out disambiguation so as to avoid an error propagation problem in an iterative disambiguation process. A neuro-linguistic model is adopted to automatically generate characteristics used by training and testing so as to avoid the manual selection and construction of characteristics.

Description

technical field [0001] The invention relates to a method for marking part of speech of text by using a computer, and belongs to the technical field of information processing. Background technique [0002] At present, no unsupervised part-of-speech tagging method based on Error-Correcting Output Codes (ECOC) and automatic generation of training and testing features has been found, but there is an unsupervised part-of-speech tagging method for manually generating training and testing features. There are also supervised part-of-speech tagging methods based on automatic generation of training and test features, and this method is completely different from these methods. [0003] Part-of-Speech tagging or POS tagging, also known as part-of-speech tagging or tagging for short, refers to marking a correct part of speech for each word in a sentence, that is, to determine whether each word is a noun, verb, adjective or other Part of speech process. Correct part-of-speech tagging is...

AI Technical Summary

Problems solved by technology

[0008] Purpose of the invention: In order to overcome the deficiencies in the prior art, the present invention provides an unsupervised part-of-speech tagging method based on error-correcting output coding without disambiguation, which can solve the problem of part-of-speech tagging in languages ​​where it is difficult to obtain tagged corpus Framework, to achieve part-of-speech tagging, and to facilitate the development of a series of subsequent applications (such as named entity recognition, information extraction)

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