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Extraction method of semantic relation between Chinese entities

A semantic relationship and entity technology, applied in the field of text processing, can solve the problems of complexity and low performance, and achieve the effect of improving precision and recall rate, reducing quantity, and improving overall performance

Active Publication Date: 2012-11-28
SUZHOU UNIV
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Problems solved by technology

Although this method is fast and effective, its relation extraction performance is low due to the complexity and variability of the semantic relation representation between entities.

Method used

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  • Extraction method of semantic relation between Chinese entities
  • Extraction method of semantic relation between Chinese entities
  • Extraction method of semantic relation between Chinese entities

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Experimental program
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Embodiment Construction

[0053] For the sake of clarity, the English abbreviations and terms appearing below are explained.

[0054] Syntax tree: Syntactic Parse Tree refers to the hierarchical relationship between different components of natural language sentences (such as vocabulary, parts of speech, phrases and clauses, etc.);

[0055] Relation tree: Relation Tree, the part that can express the structured information of entity relationship instances in the syntax tree;

[0056] The shortest path contains the tree: Shortest Path-enclosed Tree, SPT, in the syntax tree, connects the shortest path between two entities and the parts it contains, also known as the SPT tree;

[0057] Accuracy: Precision refers to the percentage of correct relationship instances among the relationship instances between entities identified by the system;

[0058] Recall rate: Recall refers to the percentage of correct inter-entity relationship instances identified by the system to all relationship instances;

[0059] F1 p...

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Abstract

The invention discloses an extraction method of a semantic relation between Chinese entities. The extraction method comprises the following steps of: carrying out syntactic analysis on natural statements to determine a complete syntactic tree of the natural statements; extracting a shortest path containing tree between two Chinese entities from the complete syntactic tree; extracting a path verb nearest to a second Chinese entity from the shortest path containing tree; respectively acquiring the semantic information of the two Chinese entities and the path verb; adding the three acquired semantic information into a root node of the shortest path containing tree according to a preset rule to determine the expanded shortest path containing tree to be a natural statement relation tree; and carrying out relation classification on the relation tree by utilizing a prestored classification model. According to the extraction method of the semantic relation between Chinese entities, which is disclosed by the invention, the relation tree contains abundant structured information and lexical semantic information and has better generality and semantic relation extraction overall performance, the dependence degree of a large-scale corpus is relieved, and meanwhile, the calculated amount of the system is lower.

Description

technical field [0001] The invention belongs to the technical field of text processing, in particular to a method for extracting semantic relations between Chinese entities. Background technique [0002] Semantic relationship extraction between named entities (referred to as entity relationship extraction or relationship extraction) is an important research content in information extraction. Its task is to extract the semantic relationship between two named entities from natural language text, such as A physical location relationship (PHYS.Located) that exists between the two entities "Clinton" (PER-Person) and "Pyongyang" (GPE-Geo-Political Entity) in the phrase "United States President Clinton's trip to Pyongyang". As an applied basic research, semantic relationship extraction between named entities is of great significance to natural language processing applications such as content understanding, question answering, automatic summarization, and information filtering. [...

Claims

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Application Information

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IPC IPC(8): G06F17/27G06F17/28
Inventor 钱龙华刘丹丹周国栋
Owner SUZHOU UNIV
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