基于大模型的智能抄清:事件要点抽取与报告生成

Intelligent chaoqing based on large models:event key point extraction and report generation

随着信息爆炸时代的到来,如何利用抄清手段高效地从海量数据中提取有价值的信息并生成准确的抄清报告成为了情报分析和推理领域的重要挑战。传统的手动抄清方法难以应对数据量庞大、多样性高的情报数据,因此需要借助自然语言技术提升抄清分析效率和准确性。提出了一种基于大模型的智能抄清方法,旨在通过事件要点抽取和报告生成,实现高效、准确和可靠的情报分析和推理。该方法利用自然语言处理技术对抄清数据进行分析,结合语法及语义信息进行文档事件要点信息抽取,基于大模型的生成能力,生成全面且内容丰富的抄清报告。

With the advent of the era of information explosion,how to efficiently extract valuable information from massive intelligence by means of chaoqing and generate accurate chaoqing reports has become an important challenge in the field of intelligence analysis and reasoning.The traditional manual chaoqing method is difficult to deal with the huge amount of data and high diversity of intelligence data,so it is necessary to use natural language technology to improve the efficiency and accuracy of chaoqing analysis.This paper proposes an intelligent chaoqing method based on a large model,which aims to extract and generate reports through event extraction.This method first uses natural language processing technology to analyze the chaoqing data,and extracts key points of document events in combination with grammatical and semantic information.Based on the generative capabilities of large models,comprehensive chaoqing reports with rich transcripts is generated.