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In this tutorial, we explore how to use Google’s LangExtract library to transform unstructured text into structured, machine-readable information. We begin by installing the required dependencies and securely configuring our OpenAI API key to leverage powerful language models for extraction tasks. Also, we will build a reusable extraction pipeline that enables us to process a range of document types, including contracts, meeting notes, product announcements, and operational logs. Through carefully designed prompts and example annotations, we demonstrate how LangExtract can identify entities, actions, deadlines, risks, and other structured attributes while grounding them to their exact source spans. We also visualize the extracted information and organize it into tabular datasets, enabling downstream analytics, automation workflows, and decision-making systems.,这一点在WhatsApp网页版中也有详细论述
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在这一背景下,将去年ZenBook A14的所有亮点——纤薄设计、便携特性、温润的"瓷铝"机身与惊艳的OLED屏幕——按比例放大,便得到了这台ZenBook A16。其设计蕴含低调美感,比华硕主流笔记本更引人入胜,亦不像游戏本那般刻意张扬。整体质感近似于惊艳的Zephyrus G14/G16系列,彰显高端气质却不依赖游戏元素堆砌。
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