--- annotations_creators: - no-annotation language: - en license: apache-2.0 task_categories: - text-generation - summarization - question-answering - feature-extraction task_ids: - language-modeling size_categories: - n<1K tags: - openai - chatgpt - gpt-4 - gpt-3 - sora - dall-e - ai-safety - frontier-ai - cl100k-tokens - llm-pretraining configs: - config_name: default data_files: "data/train-*.parquet" - config_name: full-corpus data_files: "data/train-*.parquet" ---
# 🌐 OpenAI Official News, Research & Landmark Publication Archive **High-fidelity web archive, structured clean texts, frontier AI safety whitepapers, architecture milestones (GPT-1 through GPT-4o, ChatGPT, Sora, DALL-E), and complete media assets from OpenAI's official news estate.** [![Hugging Face Dataset](https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-sphita%2Fopenai-news-FFD21E?style=flat-square)](https://huggingface.co/datasets/sphita/openai-news) [![License: Apache 2.0](https://img.shields.io/badge/License-Apache%202.0-blue.svg?style=flat-square)](https://opensource.org/licenses/Apache-2.0) [![cl100k Tokens](https://img.shields.io/badge/Tokens-1097.9k%20cl100k-orange?style=flat-square)](https://huggingface.co/datasets/sphita/openai-news) [![Total Articles](https://img.shields.io/badge/Articles-682%20Posts-blueviolet?style=flat-square)](https://huggingface.co/datasets/sphita/openai-news) [![GitHub Org](https://img.shields.io/badge/GitHub-sphita-181717?style=flat-square&logo=github&logoColor=white)](https://github.com/sphita) [Overview](#-overview--executive-summary) · [Corpus & Token Stats](#-comprehensive-corpus--token-statistics) · [Chunked Dataset Structure](#-chunked-dataset-structure) · [Multimodal Assets](#-multimodal-media--visual-assets-archive) · [Section Distribution](#-section--topic-distribution) · [Yearly Trends](#-historical-yearly-distribution) · [Schema](#-dataset-schema) · [Quick Start](#-quick-start-examples)
--- ## 📌 Overview & Executive Summary The **OpenAI Official News, Research & Landmark Publication Archive** is a curated, high-fidelity archive capturing the entirety of OpenAI's official publication estate ([`openai.com/news/`](https://openai.com/news/)). Maintained and published by **[Sphita AI Research](https://huggingface.co/sphita)**, this dataset is engineered for frontier LLM pretraining, domain-specific instruction tuning, alignment research, and technical retrieval-augmented generation (RAG). Spanning **11+ years of transformative AI history** (2015-12-11 to 2026-10-15), this archive documents OpenAI's evolution from an open non-profit research lab to the creator of **GPT-1, GPT-2, GPT-3, GPT-4, GPT-4o, ChatGPT, DALL-E, Codex, Whisper, and Sora**. ### Key Highlights * **Zero Container Stutter**: Custom parsing eliminates navigation noise, sidebar TOC anchors, and list container stutter. * **Exact Token Auditing**: Profiled using OpenAI's standard `cl100k_base` BPE tokenizer, measuring **1,097,877 total tokens**. * **Zero-Leak Sharded Parquet & Streaming JSONL**: Distributed in standard Hugging Face Zstandard-compressed Parquet chunks (`data/train-00000-of-0000N.parquet`, 200 articles each) and streaming JSON Lines (`data/openai_news.jsonl`). * **Chunked Multimodal Media Archives (Max 500 MiB)**: Images and screenshots are split into size-bounded shards (`media/images-0000X.tar.gz`, `media/screenshots-0000X.tar.gz`) with immutable sealed historical shards for fast incremental updates. --- ## 📊 Comprehensive Corpus & Token Statistics *Token volume calculated using OpenAI `cl100k_base` BPE tokenizer against all 682 articles.* | Metric | Clean Markdown Text | Raw Payload / Metadata | Combined Archive | | :--- | :--- | :--- | :--- | | **Total Tokens (`cl100k_base`)** | **1,097,877** | — | **1,097,877** | | **Total Words** | **838,614** | — | **838,614** | | **Total Raw Character Size** | **5,476,619 chars** (5.22 MB) | — | **5.22 MB** | | **Average Tokens per Article** | **1609.8** tokens | — | **1609.8** tokens | | **Median Tokens per Article** | **1,267** tokens | — | **1,267** tokens | | **Total Parquet Size (ZSTD-9)** | — | — | **3.13 MB** (4 shards) | | **JSONL Streaming Size** | — | — | **11.81 MB** | | **Columnar Compression Ratio** | — | — | **1.7x reduction** | --- ## 📦 Chunked Dataset Structure Parquet tables are sharded into standard chunks (up to 200 rows per shard) for parallel streaming, instant loading, and fast network transfer: | Shard Path | Format | Rows | File Size | Description | | :--- | :--- | :--- | :--- | :--- | | `data/train-00000-of-00004.parquet` | Parquet (ZSTD-9) | ≤ 200 | **1.09 MB** | Canonical Hugging Face split shard | | `data/train-00001-of-00004.parquet` | Parquet (ZSTD-9) | ≤ 200 | **1.02 MB** | Canonical Hugging Face split shard | | `data/train-00002-of-00004.parquet` | Parquet (ZSTD-9) | ≤ 200 | **0.75 MB** | Canonical Hugging Face split shard | | `data/train-00003-of-00004.parquet` | Parquet (ZSTD-9) | ≤ 200 | **0.27 MB** | Canonical Hugging Face split shard | | `data/openai_news.jsonl` | JSON Lines (UTF-8) | 682 | **11.81 MB** | Complete streaming JSONL corpus | --- ## 🖼 Multimodal Media & Visual Assets Archive Images and full-page rendering screenshots are split into strictly bounded archives (**≤ 500 MiB each**). Completed historical shards are **sealed and immutable**, ensuring incremental updates only download new media: | Asset Archive | Description | Status | File Count | Archive Size | Hugging Face Repository Path | | :--- | :--- | :--- | :--- | :--- | :--- | | **`images-00000.tar.gz`** | Cover images & inline figures | 🔒 Sealed | 982 files | **467.2 MB** | [`media/images-00000.tar.gz`](https://huggingface.co/datasets/sphita/openai-news/resolve/main/media/images-00000.tar.gz) | | **`images-00001.tar.gz`** | Cover images & inline figures | 🔒 Sealed | 1,643 files | **470.0 MB** | [`media/images-00001.tar.gz`](https://huggingface.co/datasets/sphita/openai-news/resolve/main/media/images-00001.tar.gz) | | **`images-00002.tar.gz`** | Cover images & inline figures | 🔒 Sealed | 583 files | **121.8 MB** | [`media/images-00002.tar.gz`](https://huggingface.co/datasets/sphita/openai-news/resolve/main/media/images-00002.tar.gz) | | **`screenshots-00000.tar.gz`** | Full-page browser render screenshots | 🔒 Sealed | 194 files | **96.4 MB** | [`media/screenshots-00000.tar.gz`](https://huggingface.co/datasets/sphita/openai-news/resolve/main/media/screenshots-00000.tar.gz) | | **`screenshots-00001.tar.gz`** | Full-page browser render screenshots | 🔒 Sealed | 200 files | **80.2 MB** | [`media/screenshots-00001.tar.gz`](https://huggingface.co/datasets/sphita/openai-news/resolve/main/media/screenshots-00001.tar.gz) | | **`screenshots-00002.tar.gz`** | Full-page browser render screenshots | 🔒 Sealed | 200 files | **90.0 MB** | [`media/screenshots-00002.tar.gz`](https://huggingface.co/datasets/sphita/openai-news/resolve/main/media/screenshots-00002.tar.gz) | | **`screenshots-00003.tar.gz`** | Full-page browser render screenshots | 🔒 Sealed | 88 files | **33.0 MB** | [`media/screenshots-00003.tar.gz`](https://huggingface.co/datasets/sphita/openai-news/resolve/main/media/screenshots-00003.tar.gz) | ### Unpacking Media Assets ```bash # 1. Download and unpack all chunked images (preserves images//... layout) huggingface-cli download sphita/openai-news --include "media/images-*.tar.gz" --local-dir ./ for f in media/images-*.tar.gz; do tar -xzf "$f"; done # 2. Download and unpack screenshots (preserves screenshots/.png layout) huggingface-cli download sphita/openai-news --include "media/screenshots-*.tar.gz" --local-dir ./ for f in media/screenshots-*.tar.gz; do tar -xzf "$f"; done ``` --- ## 🗂️ Section & Topic Distribution | Section Name | Article Count | Clean Words | cl100k Tokens | % of Corpus | Subject Matter & Scope | | :--- | :--- | :--- | :--- | :--- | :--- | | **Company** | 230 | 199,502 | 256,810 | 33.7% | Corporate governance, philanthropic partnerships, educational initiatives, infrastructure milestones | | **Product** | 181 | 241,205 | 330,417 | 26.5% | Public foundation model releases, ChatGPT capabilities, API platform tooling, and enterprise features | | **Safety** | 147 | 178,404 | 226,742 | 21.6% | Frontier AI safety evaluations, red teaming, preparedness framework, watermarking, and cyber defense | | **Research** | 43 | 80,913 | 105,166 | 6.3% | Fundamental deep learning theory, RL algorithms, reasoning, alignment, and model interpretability | | **Security** | 34 | 45,779 | 57,672 | 5.0% | Threat intelligence, counter-espionage investigations, disruption of malicious influence campaigns | | **Engineering** | 20 | 62,246 | 83,108 | 2.9% | Large-scale infrastructure engineering, distributed supercomputing clusters, inference optimization | | **Global Affairs** | 16 | 16,411 | 20,404 | 2.3% | International policy, multilateral governance, educational equity, economic impact studies | | **AI Adoption** | 9 | 9,364 | 11,848 | 1.3% | Real-world institutional deployments across scientific labs, enterprise systems, and classrooms | | **new platform** | 1 | 2,951 | 3,507 | 0.1% | Frontier technical documentation and releases | | **this blog** | 1 | 1,839 | 2,203 | 0.1% | Frontier technical documentation and releases | --- ## 📅 Historical Yearly Distribution | Year | Article Count | Total Words | cl100k Tokens | Major Historic Milestones | | :--- | :--- | :--- | :--- | :--- | | **2026** | 396 | 566,702 | 742,544 | Rosalind Academic Plan, Sora-2 System Cards, AI-enabled False Front Disruptions, Teens Learning & Planning | | **2025** | 85 | 91,505 | 120,816 | Sora 2 General Release, GPT-4.5 System Card, GPT-4.1 Architecture, Disney Collaboration, Sycophancy Studies | | **2024** | 180 | 166,685 | 216,929 | GPT-4o Omnimodal Model Launch, Sora World Simulator Debut, Advanced Voice Mode, Strawberry/o1 Reasoning | | **2023** | 13 | 8,624 | 10,976 | GPT-4 Landmark Launch, DALL-E 3 ChatGPT Integration, Custom GPTs, Superalignment Mission | | **2020** | 8 | 5,098 | 6,612 | GPT-3 (175B Parameters) Milestone, Scaling Laws for Neural Language Models, OpenAI API Commercial Launch | --- ## 📐 Dataset Schema | Column | Type | Description | | :--- | :--- | :--- | | `url` | `string` | Canonical permanent URL to the official OpenAI publication | | `slug` | `string` | Normalized URL slug identifier (e.g. `introducing-the-rosalind-academic-plan`) | | `title` | `string` | Publication headline | | `description` | `string` | SEO summary / meta description | | `authors` | `list` | Documented authors or corporate research collective | | `date_published` | `string` | ISO 8601 publication timestamp | | `date_modified` | `string` | ISO 8601 modification timestamp (if available) | | `categories` | `list` | Editorial categories (Research, Product, Safety, etc.) | | `tags` | `list` | Associated topic and year tags | | `word_count` | `int64` | Word count of the cleaned body text | | `character_count` | `int64` | Total character count of cleaned body text | | `cl100k_tokens` | `int64` | Exact OpenAI `cl100k_base` BPE token count | | `body_text` | `string` | Normalized plain text content | | `body_markdown` | `string` | Structured markdown with headings, code blocks, lists | | `featured_image` | `string` | Remote CDN URL for high-resolution cover image | | `featured_image_path` | `string` | Local relative filesystem path to downloaded cover image (`images//featured.*`) | | `inline_images` | `list` | Remote CDN URLs for inline architectural illustrations | | `inline_image_paths` | `list` | Local relative filesystem paths to downloaded inline images (`images//inline_*.*`) | | `screenshot_path` | `string` | Local relative filesystem path to full-page render screenshot (`screenshots/.png`) | --- ## 🚀 Quick Start Examples ### Load via Hugging Face `datasets` ```python from datasets import load_dataset # Automatically loads and concatenates all train-*.parquet shards dataset = load_dataset("{repo_id}", split="train") print(f"Total articles loaded: {len(dataset)}") sample = dataset[0] print(f"Latest: {sample['title']} ({sample['date_published']})") print(f"Tokens: {sample['cl100k_tokens']:,} cl100k") ``` ### Streaming Iteration ```python dataset = load_dataset("{repo_id}", split="train", streaming=True) for article in dataset: print(f"Title: {article['title']}") print(f"Hero Image: {article['featured_image_path']}") print(f"Screenshot: {article['screenshot_path']}") break ``` --- ## ⚖️ License & Attribution Corpus texts and assets are property of OpenAI. This dataset compilation and pipeline is archived under Apache 2.0 by **Sphita AI Research**.