Event content verification method, apparatus and storage medium based on large model

CN120145075BActive Publication Date: 2026-05-26BEIJING TOPWALK INFORMATION TECH CO LTD +1
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
BEIJING TOPWALK INFORMATION TECH CO LTD
Filing Date
2025-05-16
Publication Date
2026-05-26

AI Technical Summary

Technical Problem

Existing technologies struggle to accurately distinguish the semantics of words in different events when faced with ambiguous word meanings and complex grammatical scenarios, leading to biases in event argument extraction and low accuracy in event content verification.

Method used

By using a large model to identify events in the target text, rewriting them according to rewriting rules to form reference events with a unified structure and clear semantics, an event knowledge base is constructed, and the large model is used to compare the events to be checked with the reference events to improve the accuracy of the verification.

Benefits of technology

By leveraging the semantic understanding capabilities and rewriting processes of large-scale models, biases in event argument extraction are reduced, event representations are standardized, and the accuracy and efficiency of event content verification are improved.

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Abstract

This invention discloses a method, apparatus, and storage medium for event content verification based on a large model, belonging to the field of data processing technology. The method includes: identifying events in target text using a large model, rewriting the events in the target text according to target rewriting rules to obtain reference events; the target text is standard data that has been reviewed; storing the reference events in an event knowledge base; retrieving target reference events associated with the event to be verified from the event knowledge base based on the event to be verified; and comparing the event to be verified and the target reference events using the large model to obtain a comparison result characterizing whether the event to be verified is correct. This application utilizes the powerful semantic understanding capability of the large model to accurately identify events in standard data and rewrite the events to form structurally unified and semantically clear reference events, thereby constructing a high-quality event knowledge base and improving the accuracy of event content verification.
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