Datasets:
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a |
aa |
aah |
aahed |
aahing |
aahs |
aal |
aalii |
aaliis |
aals |
aardvark |
aardvarks |
aardwolf |
aardwolfs |
aardwolves |
aargh |
aarrgh |
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aas |
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aaugh |
ab |
aba |
abaca |
abacas |
abacavir |
abacavired |
abacaviring |
abacavirs |
abaci |
aback |
abacteremic |
abacteremicer |
abacteremicest |
abacterial |
abacterialer |
abacterialest |
abacteriuric |
abacteriuricer |
abacteriuricest |
abacus |
abacuses |
abaft |
abaka |
abakas |
abalone |
abalones |
abambulacral |
abambulacraler |
abambulacralest |
abamectins |
abamectinsed |
abamectinses |
abamectinsing |
abamp |
abampere |
abamperes |
abamps |
abandon |
abandonable |
abandonabler |
abandonablest |
abandoned |
abandoner |
abandoners |
abandoning |
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abandonments |
abandons |
abapical |
abapicaler |
abapicalest |
abarognoses |
abarognosis |
abarthroses |
abarticular |
abarticulation |
abarticulations |
abas |
abase |
abased |
abasedly |
abasement |
abasements |
abaser |
abasers |
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abasest |
abash |
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abashing |
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abashment |
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abasia |
abasias |
YAML Metadata Warning:The task_ids "text-classification-other-word-validation" is not in the official list: acceptability-classification, entity-linking-classification, fact-checking, intent-classification, language-identification, multi-class-classification, multi-label-classification, multi-input-text-classification, natural-language-inference, semantic-similarity-classification, sentiment-classification, topic-classification, semantic-similarity-scoring, sentiment-scoring, sentiment-analysis, hate-speech-detection, text-scoring, named-entity-recognition, part-of-speech, parsing, lemmatization, word-sense-disambiguation, coreference-resolution, extractive-qa, open-domain-qa, closed-domain-qa, news-articles-summarization, news-articles-headline-generation, dialogue-modeling, dialogue-generation, conversational, language-modeling, text-simplification, explanation-generation, abstractive-qa, open-domain-abstractive-qa, closed-domain-qa, open-book-qa, closed-book-qa, text2text-generation, slot-filling, masked-language-modeling, keyword-spotting, speaker-identification, audio-intent-classification, audio-emotion-recognition, audio-language-identification, multi-label-image-classification, multi-class-image-classification, face-detection, vehicle-detection, instance-segmentation, semantic-segmentation, panoptic-segmentation, image-captioning, image-inpainting, image-colorization, super-resolution, grasping, task-planning, tabular-multi-class-classification, tabular-multi-label-classification, tabular-single-column-regression, rdf-to-text, multiple-choice-qa, multiple-choice-coreference-resolution, document-retrieval, utterance-retrieval, entity-linking-retrieval, fact-checking-retrieval, univariate-time-series-forecasting, multivariate-time-series-forecasting, visual-question-answering, document-question-answering, pose-estimation
English OpenList
The largest open-source, validated English word list for NLP and games.
Dataset Description
English OpenList is a comprehensive, continuously updated dictionary of valid English words. It provides:
- 378,666+ validated English words following Scrabble-compatible rules
- Rich metadata including part of speech, definitions, and pronunciation
- Weekly updates from authoritative dictionary sources
- Version history with changelogs for every update
Why Use English OpenList?
| Use Case | Benefit |
|---|---|
| Spell Checking | High-precision word validation |
| Word Games | Scrabble/Wordle compatible list |
| NLP Training | Clean, validated vocabulary |
| Research | Transparent methodology, full provenance |
Dataset Structure
Full Word Lists (data/)
These are the complete, up-to-date word lists that most users will want to download:
data/
βββ merged_valid_words.txt # FULL valid word list (378,666+ words, one per line)
βββ merged_valid_dict.json # FULL dictionary with metadata for all valid words
βββ merged_invalid_words.txt # FULL invalid/rejected entries list
βββ merged_invalid_dict.json # FULL invalid dictionary with rejection reasons
Daily Releases (releases/)
Daily updates with changelog and statistics:
releases/
βββ {YYYY-MM-DD}/
βββ promoted_words.txt # Words promoted from invalid to valid that day
βββ update_stats.json # Statistics for the update
βββ CHANGELOG.md # Changelog for the update
Latest Update Reference (latest/)
Copy of the most recent release for convenience:
latest/
βββ promoted_words.txt
βββ update_stats.json
βββ CHANGELOG.md
Brrrdle Artifacts
Brrrdle-compatible artifacts are generated during daily automation and uploaded to:
latest/brrrdle/
data/brrrdle/
The primary Brrrdle files are words_length_{N}.json for every supported length
from 2 through 35. Each file contains metadata.curation, curated answers, and
complete validGuesses. The validGuesses array remains the full per-length
list, while answers is generated with the deterministic
stratified_quality_score_v1 method using seed 42 + length. Both arrays contain
plain word strings.
During the transition to length-specific artifacts, the legacy length-5
compatibility files brrrdle_words.txt and brrrdle_words.json are still
published. These legacy files should be removed in the next major Brrrdle
artifact update, along with any legacy-only manifest or generated README behavior.
Data Fields
Valid Dictionary Entry:
{
"word": "example",
"source": "merriam-webster",
"part_of_speech": "noun",
"definition": "one that serves as a pattern...",
"pronunciation": "ig-Λzam-pΙl",
"validation_status": "valid",
"added_date": "2026-01-12T00:00:00"
}
Validation Rules (Scrabble-Compatible)
Words are included if they:
- β Contain only lowercase letters (a-z)
- β Are recognized by Merriam-Webster Collegiate Dictionary
- β Are 2-45 characters in length
- β Are NOT proper nouns (unless commonly used as verbs)
- β Are NOT abbreviations or acronyms
Dataset Statistics
| Metric | Value |
|---|---|
| Total Valid Words | 378,666+ |
| Total Invalid Entries | 9,275,000+ |
| Update Frequency | Daily (00:00 UTC) |
| Primary Source | Merriam-Webster Collegiate Dictionary |
Usage
Python (Hugging Face Datasets)
from datasets import load_dataset
# Load the valid word list
dataset = load_dataset("english-openlist/english-openlist", split="train")
# Access words
for entry in dataset:
print(entry["word"])
Direct Download
Download the complete word lists:
# Download FULL valid words list (378,666+ words)
wget https://huggingface.co/datasets/ryanjosephkamp/english-openlist/resolve/main/data/merged_valid_words.txt
# Download FULL valid dictionary with metadata
wget https://huggingface.co/datasets/ryanjosephkamp/english-openlist/resolve/main/data/merged_valid_dict.json
# Download FULL invalid words list (for reference)
wget https://huggingface.co/datasets/ryanjosephkamp/english-openlist/resolve/main/data/merged_invalid_words.txt
# Download FULL invalid dictionary
wget https://huggingface.co/datasets/ryanjosephkamp/english-openlist/resolve/main/data/merged_invalid_dict.json
Download daily release files:
# Download a specific day's update
wget https://huggingface.co/datasets/ryanjosephkamp/english-openlist/resolve/main/releases/2026-01-19/CHANGELOG.md
Python (Raw Files)
import json
# Load word list
with open("merged_valid_words.txt", "r") as f:
words = set(line.strip() for line in f)
# Check if a word is valid
print("hello" in words) # True
print("asdf" in words) # False
# Load dictionary for metadata
with open("merged_valid_dict.json", "r") as f:
dictionary = json.load(f)
print(dictionary["example"]["definition"])
Methodology
Phase 1: Corpus Acquisition (December 2025)
Aggregated 9.8 million candidate words from 15+ open sources:
- Wiktionary (6.5M words)
- WordNet 3.1 (150K words)
- SCOWL 2020 (500K words)
- Google Books Ngrams (1M+ words)
- Collins Complete Dictionary (800K words)
Phase 2: Validation Pipeline (December 2025 - January 2026)
Multi-stage AI validation using Gemini 2.0/2.5 Flash:
- Pattern-based screening
- LLM classification with iterative convergence
- Statistical sampling for quality assurance
- Synthetic word generation and validation
Phase 3: Continuous Updates (January 2026 - Ongoing)
Daily automated pipeline:
- Discover new words from Merriam-Webster RSS feed and manual additions
- Validate ~1,000 words from invalid list against dictionary APIs
- Promote validated words to the valid list
- Update full word lists and dictionaries on Hugging Face
- Generate changelog and statistics
Citation
@dataset{english_openlist_2026,
title = {English OpenList: A Comprehensive Validated English Word List},
author = {English OpenList Project Team},
year = {2026},
publisher = {Hugging Face},
url = {https://huggingface.co/datasets/english-openlist/english-openlist}
}
License
This dataset is released under the MIT License.
The underlying word data is derived from open sources with compatible licenses.
Contact
- Issues: GitHub Issues
- Updates: Check the
releases/folder for version history
Last Updated: January 2026
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