Entity relationship extracting method of Zang language

Abstract

The invention relates to an entity relationship extracting method of the Zang language. The method comprises the following steps: extracting training linguistic data from the Zang-Chinese text linguistic data information; constructing a Zang word vector model; acquiring an entity relationship characteristic vector from the Zang word vector model; using the entity relationship characteristic vector as an input to construct an entity relationship classification model based on a neural network; and applying multiple layers of characteristic extractions to the entity relationship characteristic vector, thereby finally acquiring a Zang language entity relationship classification. The extraction of the Zang language entity relationship is achieved by constructing the Zang word vector model, researching and solving lexical semantic characteristics and sentence characteristic vector expression methods of the Zang language entity relationship, and further constructing the Zang language entity relationship classification model, accordingly increasing the accuracy in the Zang language entity relationship classification, and providing technical supports and services to the researches in the fields of the Zang language knowledge mapping, question-answering system, information extraction, information search, and the like.

Description

technical field [0001] The invention relates to a method for extracting a Tibetan entity relationship, in particular to a method for extracting a Tibetan entity relationship based on a word vector. Background technique [0002] With the rapid popularization of the Internet, especially the rapid increase of Internet users in developing countries, the number of non-English text resources on the Internet has increased rapidly, and its growth rate has far exceeded the speed of 10 years ago. Published in multiple languages. According to a survey by the Minority Language Sub-Center of the National Language Resources Monitoring and Research Center of Minzu University of China: by the end of December 2011, the total number of websites in the mainland’s minority languages ​​was about 1,250, including 840 websites in Uyghur and 146 in Tibetan. and 136 Mongolian websites. "Compared with the growth rate of Internet users nationwide, the growth rate of Internet users of ethnic minoriti...

AI Technical Summary

Problems solved by technology

In Tibetan, usually called (Dalai Lama) for (The Dalai Lama), while current search engines do not show the relationship between the two

Moreover, all search results are mainly displayed in text containing keywords, without knowledge structure representation

Therefore, we cannot get comprehensive and accurate relevant information, let alone realize the in-depth mining of information

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