Update README.md

README.md

@@ -57,14 +57,14 @@ This is a **free evaluation sample** from [CEOInterviews.ai](https://ceointervie
 | **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)
+**Sample Date Range:** 3 months (August — Nov 2025)
+**Full Dataset:** 2007-Present (updated daily)
 
 ---
 
 ## 💡 The Problem We Solve
 
-> *"Alpha lives in unguarded moments."*
+> **Alpha lives in unguarded moments.**
 
 The media playbook for executives has fundamentally shifted:
 
@@ -92,18 +92,9 @@ 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_quotes = requests.get(f"{API}/quotes/", params={"entity_id": 15847, "keyword": "recession"}, headers=headers).json()
+dimon_quotes = requests.get(f"{API}/quotes/", params={"entity_id": 12903, "keyword": "recession"}, 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]}...")
 
@@ -133,59 +124,45 @@ seen before... the Fed has to meet this now..."
 
 ## 📊 Dataset Schema
 
-### `transcripts`
+Each row is a **notable quote** with full context about the executive and source video.
 
 | Field | Type | Description |
 |-------|------|-------------|
-| `transcript_id` | int | Unique identifier |
-| `entity_id` | int | Executive ID (join to entities) |
-| `entity_name` | string | Executive name |
+| `quote_text` | string | **The quote itself** |
+| `entity_simple_name` | string | Normalized name (e.g., "Jensen Huang") |
+| `entity_title` | string | Job title |
+| `entity_profile_pic_url` | string | Profile image URL |
+| `post_video_thumbnail_url` | string | Video thumbnail URL |
+| `post_appearance_date` | date | **When executive actually spoke** ⭐ |
+| `company_logo_url` | string | Company logo URL |
+| `entity_institution` | string | Company/organization |
+| `post_title` | string | Video/podcast title |
+| `post_source_url` | string | Original YouTube URL |
+| `quote_is_notable` | bool | AI-flagged as significant |
+| `quote_is_controversial` | bool | AI-flagged as controversial |
+| `quote_is_financial_policy` | bool | Market/policy relevant |
+| `quote_topics` | list | Extracted topics (e.g., `["tariffs", "trade"]`) |
+| `quote_entities` | list | People mentioned |
+| `quote_companies` | list | Companies mentioned |
+| `post_description` | string | Video description |
+| `post_source_created_at` | datetime | When video was published |
+| `quote_timestamp_from_tx` | string | Timestamp in video (e.g., `00:01:48,000`) |
+| `quote_created_at` | datetime | When we extracted this quote |
+| `entity_id` | int | Executive ID |
+| `entity_name` | string | Full name |
+| `entity_is_politician` | bool | Is a political figure |
+| `entity_is_company_leader` | bool | Is a corporate executive |
+| `entity_is_top_influencer` | bool | High-profile individual |
+| `company_id` | int | Company ID |
 | `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 |
+| `post_id` | int | Source video/transcript ID |
+| `post_appearance_lag_days` | int | Days between appearance and publish |
+| `post_thumbnail_quality_review_score` | float | AI thumbnail verification (0-1) |
+| `post_transcript_quality_review_score` | float | AI transcript verification (0-1) |
+| `post_transcript_length_chars` | int | Transcript length in characters |
+| `post_has_transcript` | bool | Has full transcript available |
+| `transcript_demo_only_request_licensed_access` | list | **Transcript preview** (first 20 lines) |
+| `quote_id` | int | Unique quote identifier |
 
 ---
 
@@ -229,33 +206,6 @@ We don't just give you transcripts—we extract the **market-moving moments**:
     "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
@@ -277,9 +227,9 @@ ai_mentions = [r for r in ds['train'] if 'artificial intelligence' in r['transcr
 | Metric | This Sample | Full Dataset |
 |--------|-------------|--------------|
 | Executives | 9 | **20,000+** |
-| Transcripts | ~200 | **100,000+** |
-| Quotes | ~1,000 | **400,000+** |
-| Date Range | 2020-2022 | **2015-Present** |
+| Transcripts | ~1400 | **100,000+** |
+| Quotes | ~7,000 | **400,000+** |
+| Date Range | 2025 | **2007-Present** |
 | Updates | Static | **Daily** |
 | API Access | ❌ | ✅ 1,000 req/min |
 | Custom Entities | ❌ | ✅ On request |