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Datasets:
cstr
/
en-wiktionary-sqlite-all

Tasks:
Text Retrieval
Languages:
English
Size:
1M<n<10M
Tags:
wiktionary
dictionary
english
linguistics
morphology
semantics
License:
Dataset card Files
xet
Community
en-wiktionary-sqlite-all
File size: 3,902 Bytes 
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---
license: cc-by-sa-3.0
task_categories:
- text-retrieval
language:
- en
tags:
- wiktionary
- dictionary
- english
- linguistics
- morphology
- semantics
- normalized
- lossless
size_categories:
- 1M<n<10M
---

# English Wiktionary - TRULY LOSSLESS Normalized SQLite Database

This is a **100% lossless, fully normalized** SQLite database of English Wiktionary, capturing EVERY field from the `cstr/en-wiktionary-extracted-all` dataset.

## 🎯 Key Features

- **✅ 100% Lossless**: ALL fields captured including:
  - 🔗 **Wikilinks** in definitions (semantic connections)
  - 📝 **Qualifiers** (e.g., "archaic", "US", "informal")
  - 🏷️ **Sense IDs** (unique identifiers)
  - 🌐 **Wikidata IDs** (for semantic web linking)
  - 📚 **Attestations** (historical citations)
  - 🎭 **Head templates** (morphological data)
  - 📖 **Info templates** (structured metadata)
- **⚡ Fast Queries**: Fully indexed schema for sub-20ms queries
- **🔗 Complete Semantic Web**: All relations preserved with sense-level granularity
- **📱 Mobile-ready**: Optimized for sqflite (Flutter) and local DB use cases

## 📊 Database Statistics

- **Entries**: 1,427,190
- **Word Senses**: 1,705,177
- **Definitions (Glosses)**: 1,753,523
- **Wikilinks**: 3,476,476
- **Sense IDs**: 1,705,177
- **Qualifiers**: Embedded in senses
- **Translations**: 3,394,497
- **Word Forms**: 944,222
- **Head Templates**: 1,424,086
- **Pronunciations**: 519,225
- **Examples**: 708,542
- **Attestations**: 12,434
- **Wikidata IDs**: 6,652
- **Synonyms**: 573,360
- **Antonyms**: 36,234
- **Hypernyms**: 23,416
- **Hyponyms**: 4,576

## 🏗️ Database Schema (40+ Tables)

### New Tables (vs Previous Versions)
- **head_templates**: Morphological templates
- **entry_wikipedia**: Wikipedia cross-references
- **sense_links**: Wikilinks in definitions
- **sense_raw_tags**: Unstructured tags
- **sense_wikidata**: Wikidata identifiers
- **sense_wikipedia**: Wikipedia at sense level
- **attestations**: Historical citations
- **info_templates**: Structured metadata

### Core Tables
- **entries**: Core word data with etymology
- **senses**: Definitions with qualifier, senseid, head_nr
- **translations**: Multi-language translations
- **examples**: Usage examples
- **semantic relations**: hypernyms/hyponyms/meronyms/holonyms/coordinate_terms

## 📖 Usage

### Download
```python
from huggingface_hub import hf_hub_download
import sqlite3
import gzip
import shutil

# Download compressed database
db_gz_path = hf_hub_download(
    repo_id="cstr/en-wiktionary-sqlite-all",
    filename="en_wiktionary_normalized_all.db.gz",
    repo_type="dataset"
)

# Decompress
db_path = db_gz_path.replace('.gz', '')
with gzip.open(db_gz_path, 'rb') as f_in:
    with open(db_path, 'wb') as f_out:
        shutil.copyfileobj(f_in, f_out)

# Connect
conn = sqlite3.connect(db_path)
```

### Example Queries

```python
# Get definition with wikilinks for "dog"
cursor.execute('''
    SELECT g.gloss_text, GROUP_CONCAT(l.link_text, ', ') as links
    FROM entries e
    JOIN senses s ON e.id = s.entry_id
    JOIN glosses g ON s.id = g.sense_id
    LEFT JOIN sense_links l ON s.id = l.sense_id
    WHERE e.word = ? AND e.lang = 'English'
    GROUP BY g.id
''', ('dog',))

# Get words with specific qualifier (e.g., "archaic")
cursor.execute('''
    SELECT e.word, s.qualifier, g.gloss_text
    FROM entries e
    JOIN senses s ON e.id = s.entry_id
    JOIN glosses g ON s.id = g.sense_id
    WHERE s.qualifier LIKE '%archaic%'
    LIMIT 10
''')

# Find Wikidata ID for a sense
cursor.execute('''
    SELECT e.word, w.wikidata_id
    FROM entries e
    JOIN senses s ON e.id = s.entry_id
    JOIN sense_wikidata w ON s.id = w.sense_id
    WHERE e.word = ?
''', ('cat',))
```

## 📜 License

CC-BY-SA 4.0 (same as source)

## 🔄 Version

This is a **truly lossless** version capturing all 40+ fields from the source data.