# I am the Watcher. I am your guide through this vast new twtiverse.
# 
# Usage:
#     https://watcher.sour.is/api/plain/users              View list of users and latest twt date.
#     https://watcher.sour.is/api/plain/twt                View all twts.
#     https://watcher.sour.is/api/plain/mentions?uri=:uri  View all mentions for uri.
#     https://watcher.sour.is/api/plain/conv/:hash         View all twts for a conversation subject.
# 
# Options:
#     uri     Filter to show a specific users twts.
#     offset  Start index for quey.
#     limit   Count of items to return (going back in time).
# 
# twt range = 1 1
# self = https://watcher.sour.is/conv/ipathsq
yue-fang-readfog
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RAE：通過檢索增強來完成事件提取任務**
Decompose, Enrich, and Extract! Schema-aware Event Extraction using LLMs 大型語言模型（LLMs）在處理自然語言數據方面能力卓越，能從多樣的文本資源中高效提取知識，助力情境洞察與決策支持。但其易產生幻覺的弱點，導致上下文信息失真，引發擔憂。本研究聚焦於利用 LLMs 自動提取事件，創新性地將任務拆分爲事件檢測與事件論 ⌘ Read more