Entity disambiguation method and device based on UCL knowledge space

Abstract

The invention provides an entity disambiguation method and device based on a UCL knowledge space, and the method comprises the steps: firstly constructing a basic knowledge base, and completing the construction of the UCL knowledge space; then obtaining a candidate entity set related to the entity to be disambiguated from the UCL knowledge space, and generating an embedded representation of the candidate entity and the entity to be disambiguated by using a word vector representation method; then extracting concept features of an entity to be disambiguated and contexts thereof, and extracting features of contexts of candidate entities; finally, the four vector representations generated previously are used as input, a self-attention matching network based on a deep structured semantic matching model DSSM is adopted, and the matching degree is obtained; and obtaining a final disambiguation result according to the sorting of matching results, and completing entity linking between the entities in the text and the entities in the UCL knowledge space. According to the method and the device, the problem of less entity related information in the short text can be solved, and the entity disambiguation accuracy can be improved.

Description

technical field

[0001] The invention relates to a UCL knowledge space-based entity disambiguation method and device, and belongs to the technical field of knowledge map construction in the Internet. Background technique

[0002] With the rapid development of the Internet, the number of online news has increased sharply, and the knowledge information contained in the news has become more and more complicated. There is an urgent need for a suitable carrier to effectively store and manage news information. The knowledge map can associate entities together to form a graph database by constructing "entity-relationship-entity" triples and "entity-attribute (value)" key-value pairs. The unified content label UCL (Uniform Content Label) defined by the national standard "Uniform Content Label Format Specification" (GB / T 35304-2017) can provide rich semantic information, and its content format includes who, what, where, Elements that are highly consistent with news events such as wha...

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