Geographical science domain named entity recognition method

Abstract

The invention discloses a geographical science domain named entity recognition method, which is used for recognizing geographical science core term entities and geographical location entities. The method mainly comprises three steps of (1) establishing a geographical science domain dictionary, and using a new word discovery algorithm to identify new words in the geographical science domain in an unsupervised way; (2) training and testing based on a conditional random field (CRF) model and a multichannel convolutional neural network (MCCNN) model; (3) carrying out error correcting and fusion on entities recognized by the models by using a rule-based method. According to the geographical science domain named entity recognition method, the new words of the domain are identified as the dictionary in an unsupervised way by using the new word discovery algorithm, so that the work distinguishing effect is improved. The semantic vectors of the words are learnt from large-scale unmarked data in an unsupervised way, and basic characteristics of the words are synthesized and are taken as the input characteristics of the MCCNN model, so that manual selection and construction of the characteristics are avoided. The predicting results of the two models are fused by means of a custom rule, so that the problem of error marking in a recognition process can be corrected.

Description

technical field [0001] The invention belongs to the technical field of information extraction, in particular to a named entity recognition method in the field of geography. Background technique [0002] Named Entity Recognition (NER) is the basic link of information extraction, which is applied to follow-up tasks, such as relationship extraction and entity linking, and is widely used in natural language processing fields such as automatic question answering and machine translation. [0003] For the geography college entrance examination question and answer system, it is particularly important to construct a geography knowledge map for basic education. In order to acquire knowledge from geographic discipline resources and build geographic discipline knowledge graphs, named entity recognition is usually the primary task. This patent is the first attempt to perform named entity recognition for the field of geography, and the extracted named entity categories include core terms...

AI Technical Summary

Problems solved by technology

Named entity recognition in the field of geography not only has the inherent difficulties of Chinese named entity recognition, but also faces many problems such as the difficulty of word segmentation in the field and the lack of large-scale manual annotation training corpus.

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