Update README.md

README.md

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-license: cc-by-nd-4.0
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+---
+license: cc-by-nd-4.0
+task_categories:
+- text-generation
+- text-classification
+- feature-extraction
+- question-answering
+tags:
+- finance
+- nlp
+- transcripts
+- ceo
+- executives
+- sentiment-analysis
+- hedge-fund
+- alternative-data
+- earnings-calls
+- podcasts
+- interviews
+- market-signals
+- quant
+- fed
+- macro
+size_categories:
+- 100K<n<1M
+---
+
+<div align="center">
+
+# 🎙️ CEO Transcripts — Verified Executive Interviews
+
+### The World's Largest Database of Verified C-Suite Transcripts
+
+[![Website](https://img.shields.io/badge/🌐_Website-ceointerviews.ai-blue?style=for-the-badge)](https://ceointerviews.ai)
+[![API](https://img.shields.io/badge/📚_API_Docs-Available-green?style=for-the-badge)](https://ceointerviews.ai/api_docs/)
+[![Contact](https://img.shields.io/badge/📧_Contact-lucas@ceointerviews.ai-red?style=for-the-badge)](mailto:lucas@ceointerviews.ai)
+
+**20,000+ Executives** · **100,000+ Transcripts** · **400,000+ Quotes** · **S&P 500 + NASDAQ + Global Leaders**
+
+</div>
+
+---
+
+## 🔥 What's In This Sample?
+
+This is a **free evaluation sample** from [CEOInterviews.ai](https://ceointerviews.ai) featuring **9 of the most market-moving voices** in finance, tech, and policy.
+
+| Executive | Role | Why They Matter |
+|-----------|------|-----------------|
+| **Jensen Huang** | CEO, NVIDIA | Every AI demand signal moves $3T in market cap |
+| **Jerome Powell** | Chair, Federal Reserve | His words move trillions—quants build NLP models on Fed language |
+| **Elon Musk** | CEO, Tesla | Highest search volume globally, 3-hour podcast appearances |
+| **Warren Buffett** | CEO, Berkshire Hathaway | Most famous investor alive, legendary annual meeting Q&As |
+| **Donald Trump** | 45th & 47th President | Most searched political figure globally, 3-hour Rogan appearance, tariff policy signals move markets |
+| **Mark Zuckerberg** | CEO, Meta | Podcast king—Rogan, Fridman, unscripted strategy reveals |
+| **Jamie Dimon** | CEO, JPMorgan | Banking bellwether, "hurricane" recession calls move markets |
+| **Cathie Wood** | CEO, ARK Invest | Retail trader icon, daily commentary on disruptive innovation |
+| **Ray Dalio** | Founder, Bridgewater | Hedge fund legend, macro frameworks every quant knows |
+
+**Sample Date Range:** 2020-2022  
+**Full Dataset:** 2015-Present (updated daily)
+
+---
+
+## 💡 The Problem We Solve
+
+> *"Alpha lives in unguarded moments."*
+
+The media playbook for executives has fundamentally shifted:
+
+| Old Playbook | New Reality |
+|--------------|-------------|
+| Scripted earnings calls | 3-hour Joe Rogan podcasts |
+| PR-approved press releases | Unscripted Lex Fridman interviews |
+| Quarterly investor days | Off-the-cuff conference Q&As |
+
+**The signal is there. But it's buried in 10,000+ hours of fragmented audio.**
+
+CEOInterviews.ai transforms this chaos into structured, queryable, backtestable data.
+
+---
+
+## 🎯 Example: Powell vs Dimon on Recession Risk
+
+**Research Question:** *"What did Jerome Powell and Jamie Dimon say about recession risk in 2022?"*
+
+### Using Our API:
+
+```python
+import requests
+
+API = "https://ceointerviews.ai/api"
+headers = {"X-API-Key": "your_api_key"}
+
+# Step 1: Find entity IDs by name
+powell = requests.get(f"{API}/entities/", params={"keyword": "Jerome Powell"}, headers=headers).json()
+dimon = requests.get(f"{API}/entities/", params={"keyword": "Jamie Dimon"}, headers=headers).json()
+
+powell_id = powell["results"][0]["id"]  # 15847
+dimon_id = dimon["results"][0]["id"]    # 12903
+
+# Step 2: Get their quotes on "recession"
+powell_quotes = requests.get(f"{API}/quotes/", params={"entity_id": powell_id, "keyword": "recession"}, headers=headers).json()
+dimon_quotes = requests.get(f"{API}/quotes/", params={"entity_id": dimon_id, "keyword": "recession"}, headers=headers).json()
+
+# Step 3: Compare what they said
+for q in powell_quotes["results"][:3]:
+    print(f"[Powell {q['source_created_at'][:10]}] {q['text'][:150]}...")
+
+for q in dimon_quotes["results"][:3]:
+    print(f"[Dimon {q['source_created_at'][:10]}] {q['text'][:150]}...")
+```
+
+### Sample Output:
+
+```
+[Powell 2022-06-15] "We're not trying to induce a recession now, let's be clear about that. 
+We're trying to achieve 2% inflation..."
+
+[Dimon 2022-06-01] "You know, I said there's storm clouds but I'm going to change it... 
+it's a hurricane. Right now, it's kind of sunny, things are doing fine..."
+
+[Powell 2022-09-21] "We have got to get inflation behind us. I wish there were a painless 
+way to do that. There isn't..."
+
+[Dimon 2022-09-26] "This is serious stuff... it's a different environment than we've ever 
+seen before... the Fed has to meet this now..."
+```
+
+**This is the alpha.** Dimon called the "hurricane" 2 weeks before Powell acknowledged pain was coming.
+
+---
+
+## 📊 Dataset Schema
+
+### `transcripts`
+
+| Field | Type | Description |
+|-------|------|-------------|
+| `transcript_id` | int | Unique identifier |
+| `entity_id` | int | Executive ID (join to entities) |
+| `entity_name` | string | Executive name |
+| `company_ticker` | string | Stock ticker (e.g., "NVDA") |
+| `company_name` | string | Full company name |
+| `title` | string | Video/podcast title |
+| `description` | string | Content description |
+| `transcript` | string | **Full-text transcript** |
+| `source_url` | string | Original YouTube/source URL |
+| `thumbnail_url` | string | Video thumbnail |
+| `publish_date` | datetime | When video was published |
+| `appearance_date` | date | **When executive actually spoke** ⭐ |
+| `duration_seconds` | int | Video length |
+| `quality_score_thumbnail` | string | AI verification status |
+| `quality_score_transcript` | string | AI verification status |
+| `platform` | string | Source platform |
+| `like_count` | int | Engagement metric |
+
+### `quotes`
+
+| Field | Type | Description |
+|-------|------|-------------|
+| `quote_id` | int | Unique identifier |
+| `transcript_id` | int | Parent transcript |
+| `entity_name` | string | Who said it |
+| `company_ticker` | string | Their company |
+| `text` | string | The quote text |
+| `is_notable` | bool | AI-flagged as significant |
+| `is_controversial` | bool | AI-flagged as controversial |
+| `is_financial_policy` | bool | Market/policy relevant |
+| `topics` | list | Extracted topics |
+| `mentioned_entities` | list | People mentioned |
+| `mentioned_companies` | list | Companies mentioned |
+| `timestamp_in_video` | string | When in video (HH:MM:SS) |
+
+### `entities`
+
+| Field | Type | Description |
+|-------|------|-------------|
+| `entity_id` | int | Unique identifier |
+| `name` | string | Full name |
+| `simple_name` | string | Normalized name |
+| `title` | string | Job title |
+| `company_ticker` | string | Company ticker |
+| `company_name` | string | Company name |
+| `profile_pic_url` | string | Profile image |
+| `is_snp500` | bool | S&P 500 company |
+| `is_nasdaq` | bool | NASDAQ company |
+| `transcript_count` | int | Total transcripts available |
+
+---
+
+## ⭐ What Makes CEOInterviews Different?
+
+### 1. **Appearance Date Detection**
+
+Most datasets only have `publish_date`. But a podcast uploaded today might contain an interview from 6 months ago.
+
+**We detect when the executive actually spoke.**
+
+```python
+# Example: Interview recorded in January, published in March
+{
+    "publish_date": "2022-03-15",      # When YouTube uploaded
+    "appearance_date": "2022-01-20",   # When Buffett actually spoke ⭐
+}
+```
+
+This is critical for backtesting. You need to know **when the market could have known**, not when the video appeared.
+
+### 2. **AI + Human Verification**
+
+Every transcript passes through:
+- 🤖 **Thumbnail Analysis**: Is the executive actually in the video?
+- 🤖 **Transcript Verification**: Is this their voice, not dubbed/AI-generated?
+- 🤖 **Quality Scoring**: Is the transcript complete and accurate?
+
+**No deepfakes. No dubbing. No secondhand reporting.**
+
+### 3. **Structured Quote Extraction**
+
+We don't just give you transcripts—we extract the **market-moving moments**:
+
+```python
+{
+    "text": "We're seeing something we haven't seen in 40 years...",
+    "is_notable": True,
+    "is_financial_policy": True,
+    "topics": ["inflation", "monetary_policy", "fed"],
+    "timestamp_in_video": "00:23:45"
+}
+```
+
+---
+
+## 🚀 Quick Start
+
+```python
+from datasets import load_dataset
+
+# Load the sample
+ds = load_dataset("codelucas/ceo-transcripts-verified-sample")
+
+# Browse transcripts
+for row in ds['train']:
+    print(f"{row['entity_name']} ({row['company_ticker']})")
+    print(f"  📺 {row['title']}")
+    print(f"  📅 Appeared: {row['appearance_date']} | Published: {row['publish_date'][:10]}")
+    print(f"  ✅ Quality: {row['quality_score_transcript']}")
+    print()
+
+# Filter to NVIDIA transcripts
+nvidia = [r for r in ds['train'] if r['company_ticker'] == 'NVDA']
+print(f"Found {len(nvidia)} Jensen Huang transcripts")
+
+# Search for AI mentions
+ai_mentions = [r for r in ds['train'] if 'artificial intelligence' in r['transcript'].lower()]
+```
+
+---
+
+## 📈 Use Cases
+
+| Use Case | How This Dataset Helps |
+|----------|------------------------|
+| **Sentiment Alpha** | Backtest NLP signals on Fed language, CEO confidence |
+| **Event Studies** | Measure market reaction to specific statements |
+| **ESG Tracking** | Monitor executive commitments on climate, DEI |
+| **Competitive Intel** | What is Jensen saying about AMD? What is Zuckerberg saying about Apple? |
+| **Macro Signals** | Track Dalio's "changing world order" thesis evolution |
+| **LLM Fine-tuning** | Train models on authentic executive communication |
+| **Media Analysis** | How do CEOs communicate differently on Rogan vs CNBC? |
+
+---
+
+## 📊 Sample vs Full Dataset
+
+| Metric | This Sample | Full Dataset |
+|--------|-------------|--------------|
+| Executives | 9 | **20,000+** |
+| Transcripts | ~200 | **100,000+** |
+| Quotes | ~1,000 | **400,000+** |
+| Date Range | 2020-2022 | **2015-Present** |
+| Updates | Static | **Daily** |
+| API Access | ❌ | ✅ 1,000 req/min |
+| Custom Entities | ❌ | ✅ On request |
+
+---
+
+## 🔐 Get Full Access
+
+This sample is **<1%** of our full dataset.
+
+### Full Dataset Includes:
+- ✅ Every S&P 500 and NASDAQ CEO
+- ✅ Global political leaders (Presidents, Prime Ministers, Fed chairs)
+- ✅ Top AI founders (Altman, Hassabis, etc.)
+- ✅ Legendary investors (Buffett, Dalio, Ackman, Fink)
+- ✅ Daily updates
+- ✅ RESTful API with full pagination
+- ✅ CSV/JSON export for model training
+- ✅ White-glove enterprise support
+
+### Pricing
+
+| Tier | Price | Best For |
+|------|-------|----------|
+| **Researcher** | $499/mo | Academic research, small teams |
+| **Professional** | Custom | Hedge funds, trading desks |
+| **Enterprise** | Custom | Full API access, custom coverage |
+
+### Contact
+
+📧 **Email:** [lucas@ceointerviews.ai](mailto:lucas@ceointerviews.ai)  
+🌐 **Website:** [ceointerviews.ai](https://ceointerviews.ai)  
+📚 **API Docs:** [ceointerviews.ai/api_docs](https://ceointerviews.ai/api_docs/)
+
+---
+
+## 📜 License
+
+**CC-BY-NC-ND-4.0** (Creative Commons Attribution-NonCommercial-NoDerivatives 4.0)
+
+### What This Means:
+
+| ✅ Allowed | ❌ Not Allowed |
+|-----------|----------------|
+| Download and evaluate | Commercial use |
+| Academic research | Redistribute modified versions |
+| Personal projects | Resell or sublicense |
+| Cite in papers | Create derivative datasets |
+
+**For commercial use, contact [lucas@ceointerviews.ai](mailto:lucas@ceointerviews.ai)**
+
+---
+
+## 🛠️ Built By
+
+<div align="center">
+
+**Lucas Ou-Yang**  
+*Former Engineering Manager and Staff ML Engineer @Coinbase, @Tiktok, @Meta superintelligence labs*
+
+Building institutional-grade datasets for quantitative research.
+
+[![Website](https://img.shields.io/badge/Website-ceointerviews.ai-blue?style=flat-square)](https://ceointerviews.ai)
+
+</div>
+
+---
+
+## 📣 Citation
+
+If you use this dataset in research, please cite:
+
+```bibtex
+@misc{ceointerviews2024,
+  author = {Ou-Yang, Lucas},
+  title = {CEOInterviews.ai: Verified Executive Transcript Dataset},
+  year = {2024},
+  publisher = {HuggingFace},
+  url = {https://huggingface.co/datasets/codelucas/ceo-transcripts-verified-sample}
+}
+```
+
+---
+
+<div align="center">
+
+**⭐ Star this dataset if you find it useful!**
+
+Questions? Reach out at [lucas@ceointerviews.ai](mailto:lucas@ceointerviews.ai)
+
+</div>