《Hotspot Event Analysis tool》–developed based on the LLM-enhanced approach



This content originally appeared on DEV Community and was authored by zhangzib123

LLM-enhanced approach:
In event extraction, traditional techniques rely on rule templates and CRF models, whereas the LLM-enhanced approach employs prompt engineering and fine-tuning for intelligent semantic parsing.

Our company’s Hotspot Event Analysis tool developed based on the LLM-enhanced approach has effectively met user needs in practical applications.

For contextual analysis, static knowledge graphs are upgraded to dynamic Chain-of-Thought (CoT) reasoning, enabling causal evolution tracking and real-time decision-making.
The tool extensively collects information from domestic and foreign think tanks, mainstream media, internet public sentiment, and other sources to conduct event discovery and contextual analysis, gaining real-time insights into trending events. Additionally, based on specified thematic areas (such as macroeconomic forecasting, strategies of world-class enterprises, innovation and competitiveness, etc.), it performs in-depth event mining, correlation analysis, and dynamic monitoring, automatically generating analytical reports on events.


This content originally appeared on DEV Community and was authored by zhangzib123