An automatic labeling method for multi-label character relationships based on event remote supervision

Abstract

The invention discloses a multi-label character relationship automatic labeling method based on event remote supervision, which includes the following steps: collecting events that affect the character relationship; making a corresponding event labeling template; building an event template knowledge base; and performing data preprocessing; The preprocessed sentences use the event labeling template to mark events; carry out character relationship labeling; character relationship labeling results; calculate the credibility between "event" and "sentence"; calculate the sentence score; set a threshold, the Sentences with a sentence score below the threshold are discarded; the final character relationship annotation is obtained. The present invention matches the event template knowledge base to obtain the events that affect the relationship between characters, and then automatically deduces the multi-label relationship of characters according to multiple events, which can solve the multi-label problem of character relationship, can significantly improve the accuracy of multi-label character relationship labeling, and has more advantages. Excellent mobility.

Description

technical field [0001] The invention relates to the technical field of natural language relationship extraction, in particular to a method for automatically labeling multi-label character relationships based on event remote supervision. Background technique [0002] Character relationship extraction based on deep learning methods is widely used in natural language processing tasks. Deep learning methods are data-driven and require more labeled data. However, manual labeling methods require a lot of manpower and time, and the data scale cannot meet the needs of deep learning methods. Distant supervision is one of the common methods to automatically label person relationship datasets. It relies on a knowledge base containing a large number of triples, matching person-entity pairs in sentences with entity pairs in the knowledge base. However, the construction of the triple knowledge base is time-consuming and laborious, and the relationship of all entities needs to be exhaus...

AI Technical Summary

Problems solved by technology

However, the existing ESDS method only focuses on the labeling of a single person relationship label, ignoring the fact that some person relationships may have multiple labels.

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