Method and system for extracting causal relationships between affairs

Abstract

The invention relates to a method and a system for extracting causal relationships between affairs. The method comprises the following steps: segmenting a to-be-processed text through punctuations, and obtaining at least one clause; according to the clauses and predefined causal links, judging whether causal relationships exist among the clauses or not, generating a first causal set, and defining the corresponding clauses as cause fragments and result fragments respectively; according to the cause fragments and result fragments and by using dependency grammar, dividing the cause fragments and result fragments into at least one candidate event, judging causal relationships between candidate events, generating a second causal set, and obtaining sub-cause fragments and sub-result fragments corresponding to the cause fragments and result fragments; extracting sub-result fragments in the cause fragments as causes of a text core relationship, and extracting sub-cause fragments in the result fragments as results in the text core relationship. According to the method and the system, a causal relationship of a subsequent cause and a preceding result can be identified, and the cause and the result are accurately extracted, so that the effectiveness of the cause and effect relationship identification is improved.

Description

technical field [0001] This application relates to the technical field of natural language recognition, in particular to a method and system for extracting event causality. Background technique [0002] The construction of domain graphs in specific industries often requires the identification of events and the causal relationship between events. This task is also called event causality extraction. The traditional method is "during the alignment of runway 24, the nose wheel steering failure indicator sounded, and the captain pointed out that he forgot to press the nose wheel steering switch on the throttle lever." When this sentence extracts cause and effect, due to the reason "forgot to press The front wheel steering switch on the throttle lever" is at the end of the sentence, while traditional methods tend to extract the causal relationship of "cause and effect", resulting in the failure to extract the cause. [0003] In the prior art, an extraction method based on a depen...

AI Technical Summary

Problems solved by technology

[0005] The embodiment of the present application provides a method and system for extracting the causal relationship of events, so as to at least solve the problem that the specific cause and result cannot be accurately judged in the related art

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