智能内容结构化处理工具
Input Structuring CN 是一个专门为知识工作者设计的智能prompt,旨在从Markdown格式的内容中提取、组织和结构化信息,使其能够更好地在Obsidian知识库中进行分析和归档。这个工具通过系统化的方法论,将非结构化的文本内容转化为清晰、有层次的结构化知识。
从复杂的Markdown内容中精准提取核心信息、数据和洞察
将散乱信息按主题、层级和重要性进行系统化整理
优化信息在Obsidian vault中的存储和检索效率
将阅读和整理时间减少 70%
确保 100% 重要信息被捕获
统一的结构便于后续分析和引用
自动识别核心论点和关键证据
阅读理解
以知识工作者视角深度阅读内容
识别提取
识别主题、论点、数据和图表
结构组织
按重要性和逻辑关系组织信息
格式输出
生成标准化的Obsidian格式文档
首先总结作者的核心信息和支撑论点,形成一段完整的逻辑概述
输出位置:### Key Logic 部分
分析内容的不同主题或方面,提取每个主题下的具体细节
主题识别
细节提取
图表关联
按照Obsidian语法规范格式化输出内容
标题层级
实体链接
数字高亮
图片嵌入
根据内容生成至少10个相关标签,涵盖关键词、主题、实体等
### Key Logic
作者/信息源的核心信息用一段完整逻辑表达
### 第一个部分的主旨句
- 第一部分的细节1
- 第一部分的重要细节2
- (中文图片标题)
- ![[image.jpg]]
> [!table] 表格标题
> - 表格的关键发现
> - 值得注意的数据点
### 第二个部分的主旨句
- 第二部分的细节
- 更深层的信息
- 支撑数据:123亿美元
- 相关公司:[[Apple|苹果]]
#tag1 #tag2 #tag3 ... (至少10个)
[[Company Name]]
基础格式:英文实体名
[[Alphabet|Google]]
别名格式:正式名|常用名
[[Nvidia|英伟达]]
中文别名:英文名|中文名
==123==亿美元
数字+单位:仅高亮数字
增长==15.5==%
百分比:仅高亮数值
[[S&P500]]
含数字的实体:不高亮
> [!table] 表格标题
> - 关键发现1
> - 关键发现2
不嵌套在列表中,顶格书写
• 最少生成10个标签
• 全部使用英文
• 涵盖关键词/主题/实体
• 放置在文档末尾
• 格式:#tag_name
❌ 错误示例
✅ 正确示例
这是一个真实使用场景,展示了如何将一份高盛的研究报告原文,通过本工具转化为结构化的Obsidian笔记。
点击查看 Prompt 原文# GOAL Kickstart - Dovish and De-escalation - Markets embrace a Goldilocks Backdrop
Last week increased expectations of a more dovish Fed ([Exhibit 1](...)), de-escalation of Middle East tensions ([Exhibit 2](...)) and progress in U.S. trade negotiations (including removal of section 899) supported growth pricing across assets. [Our Economists pulled forward their forecast for the next cut to September](...) and reduced their terminal rate forecast to 3-3.25%. Indeed, our PC1 "Global growth" factor improved last week despite deteriorating macro surprises, especially in the US with [Personal spending](...), [New home sales](...), and [Consumer confidence](...) below consensus last week ([Exhibit 3](...)). With greater expectation of a more dovish Fed, this created a "Goldilocks" regime and supported risky assets and a large re-set in cross-asset implied vol, which boosted risk appetite (our [Risk Appetite Indicator](...) rebounded to 0.3, [Exhibit 10](...)) and US equities to a new all-time high. This Thursday's labour market data could be critical to sustain the positive momentum - [our economists expect 85k for non-farm payrolls, below consensus of +113k](...). The bullish growth repricing was broad geographically, with equities outperforming bonds and cyclicals outperforming defensives across regions ([Exhibit 4](...)). On the other hand, [the rally in USD HY has been led by defensive sectors](...) and there has been more regional dispersion in inflation pricing.
Expectations for equity fundamentals have been under less pressure recently. Consensus EPS revisions have turned less negative in most regions over the past month, and have turned positive for the US market ([Exhibit 5](...)). The Q2 earnings season will be a key focus for investors - our [US strategists note a relatively low bar to beat (consensus expects 4% EPS growth in 2Q, down from 12% in 1Q) but expect important insights on how companies are adjusting to increased tariff rates](...). Implied equity correlations have been falling since April across markets, reflecting investor expectations of more dispersion into the earnings season and fading macro risk - the S&P 500 and Nasdaq 100 implied correlations are now at the 17th/10th percentile since 2020 respectively - this is much in contrast to EURO STOXX 50 ([Exhibit 6](...)). Reverse dispersion trades appear attractive as a macro hedge against a larger growth backdrop deterioration over the summer.
Our asset allocation remains neutral but focused on [diversification both across regions and styles](...) into the summer. We also [continue to recommend option hedges](...): with markets pricing a more "Goldilocks" backdrop, we think USD HY puts/CDS payers looks attractive to hedge a stagflationary shock, while rates payers look attractive to hedge a more reflationary rebound. We also highlight calls/risk-reversals on Euro Area Banks (SX7E) and collars on MSCI EM to hedge a reversal in positioning.
# Dovish and De-escalation - Markets embrace a Goldilocks Backdrop
#### Exhibit 1: Markets are pricing more dovish Fed
Option-implied probability of Fed rates over the next 12 months
[](...)
#### Exhibit 2: Markets have priced lower geopolitical risk
[](...)
#### Exhibit 3: Last week, markets priced higher growth expectations despite worsening macro surprises
[](...)
#### Exhibit 4: Growth repricing was broad across regions
Average 1y z-score of equity vs. bonds, cyclical vs. defensives, credit spreads, 10y inflation swap
[](...)
#### Exhibit 5: Earnings revisions have improved across most regions and turned positive in the US
1-month FY2 EPS revision
[](...)
#### Exhibit 6: Implied correlation has come down since April
3m 50-delta implied correlation
[](...)
高盛(Goldman Sachs)分析师认为,上周市场在美联储(Fed)转向鸽派、中东局势(Middle East tensions)降温以及美国贸易谈判(U.S. trade negotiations)取得进展的共同作用下,呈现出一种“金发女孩情景”(Goldilocks Backdrop),即尽管宏观经济数据出现恶化,但市场仍对增长抱有积极定价,这推动了风险资产(Risk Assets)的上涨和美国股市(US equities)创下新高,同时高盛建议在此背景下,投资者应关注分散化(Diversification)并采取期权对冲(Option Hedges)策略。
市场正在定价更为鸽派的美联储
市场已将更低的地缘政治风险定价
上周市场定价更高的增长预期,尽管宏观意外恶化
盈利修正在大多数区域有所改善,并在美国转为正向
隐含相关性自April以来有所下降
准确识别和提取核心信息,避免冗余
清晰的层级关系和逻辑组织
标准化格式便于后续引用和分析
上下文理解
基于内容语境判断信息重要性
自适应提取
根据内容类型调整处理策略
关联性分析
自动识别信息间的逻辑关系
节省时间
自动化处理减少手动整理工作
提升质量
标准化输出保证信息完整性
增强协作
统一格式便于团队知识共享
多语言支持
扩展到更多语言的内容处理
智能分析增强
深度学习优化信息提取算法
集成扩展
与更多工具和平台无缝对接
Input Structuring CN - 智能内容结构化工具
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