Datasets:

cstr
/

de-wiktionary-sqlite-normalized

	---
	license: cc-by-sa-4.0
	task_categories:
	- text-retrieval
	- text-generation
	language:
	- de
	tags:
	- wiktionary
	- dictionary
	- german
	- linguistics
	- morphology
	- semantics
	- normalized
	size_categories:
	- 100K<n<1M
	---

	# German Wiktionary - Normalized SQLite Database

	A fully normalized, production-ready SQLite database of German Wiktionary with complete linguistic information and optimized query performance.

	## 🎯 Key Features

	- ✅ Zero data loss: All information from original Wiktionary preserved
	- ⚡ Lightning-fast queries: Comprehensive indexing (< 5ms typical queries)
	- 🔍 Full grammatical analysis: Complete inflection paradigms, word forms, 185 unique grammatical tags
	- 🔗 Semantic relations: Synonyms, antonyms, derived/related terms
	- 🌍 Multi-language: Translations to 100+ languages
	- 📱 Mobile-ready: Optimized for Flutter/Dart apps on all platforms
	- 🗣️ Pronunciation: IPA, audio files, rhymes
	- 📚 Rich examples: Usage examples with citations
	- 🎓 Proper normalization: Tags/topics/categories deduplicated (3NF)

	## 📊 Database Statistics

	- Entries: 970,801 German words
	- Word senses: 3.1M+ definitions with glosses
	- Translations: 1.1M+ translations
	- Word forms: 6.1M+ inflected forms
	- Pronunciations: 2.3M+ IPA/audio entries
	- Examples: 427K+ usage examples
	- Unique tags: 185 grammatical tags
	- Unique topics: 58 domain topics
	- Unique categories: 352 Wiktionary categories
	- File size: ~3.6 GB (uncompressed), ~1.8 GB (compressed)

	## 🏗️ Database Schema

	### Lookup Tables (Deduplicated)
	- tags: Grammatical tags (nominative, plural, past, etc.)
	- topics: Domain topics (biology, law, sports, etc.)
	- categories: Wiktionary categories

	### Core Tables
	- entries: Main word entries
	- senses: Word senses/meanings
	- glosses: Definitions for each sense
	- examples: Usage examples with citations

	### Morphology
	- forms: All inflected forms (declensions, conjugations)
	- form_tags: Many-to-many: forms ↔ grammatical tags
	- hyphenations: Syllable breaks

	### Phonology
	- sounds: IPA pronunciations, audio URLs, rhymes
	- sound_tags: Pronunciation variants

	### Semantics
	- synonyms: Synonymous words
	- antonyms: Opposite words
	- derived_terms: Morphologically derived words
	- related_terms: Semantically related words
	- synonym_tags/synonym_topics: Synonym metadata

	### Translation
	- translations: Translations to other languages
	- translation_tags: Translation grammatical tags

	### Metadata
	- entry_tags: Word-level tags
	- entry_categories: Wiktionary categories
	- sense_tags/sense_topics/sense_categories: Sense-level metadata

	## 📖 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/de-wiktionary-sqlite-normalized",
	filename="de_wiktionary_normalized.db",
	repo_type="dataset"
	)

	# Decompress if needed
	if db_gz_path.endswith('.gz'):
	db_path = db_gz_path[:-3]
	with gzip.open(db_gz_path, 'rb') as f_in:
	with open(db_path, 'wb') as f_out:
	shutil.copyfileobj(f_in, f_out)
	else:
	db_path = db_gz_path

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

	### Python Examples
	```python
	import sqlite3

	conn = sqlite3.connect('de_wiktionary_normalized.db')
	cursor = conn.cursor()

	# Example 1: Get all inflections with grammatical tags
	cursor.execute('''
	SELECT f.form_text, GROUP_CONCAT(t.tag, ', ') as tags
	FROM entries e
	JOIN forms f ON e.id = f.entry_id
	LEFT JOIN form_tags ft ON f.id = ft.form_id
	LEFT JOIN tags t ON ft.tag_id = t.id
	WHERE e.word = ? AND e.lang = 'Deutsch'
	GROUP BY f.id
	''', ('Haus',))

	for form, tags in cursor.fetchall():
	print(f"{form}: {tags}")

	# Example 2: Get synonyms
	cursor.execute('''
	SELECT s.synonym_word
	FROM entries e
	JOIN synonyms s ON e.id = s.entry_id
	WHERE e.word = ? AND e.lang = 'Deutsch'
	''', ('schnell',))

	synonyms = [row[0] for row in cursor.fetchall()]
	print(f"Synonyms: {synonyms}")

	# Example 3: Get IPA pronunciation
	cursor.execute('''
	SELECT s.ipa
	FROM entries e
	JOIN sounds s ON e.id = s.entry_id
	WHERE e.word = ? AND s.ipa IS NOT NULL
	''', ('Haus',))

	print("IPA:", [row[0] for row in cursor.fetchall()])

	# Example 4: Get definitions
	cursor.execute('''
	SELECT g.gloss_text
	FROM entries e
	JOIN senses se ON e.id = se.entry_id
	JOIN glosses g ON se.id = g.sense_id
	WHERE e.word = ? AND e.lang = 'Deutsch'
	''', ('Liebe',))

	print("Definitions:")
	for (gloss,) in cursor.fetchall():
	print(f" - {gloss}")

	# Example 5: Get English translations
	cursor.execute('''
	SELECT t.word
	FROM entries e
	JOIN translations t ON e.id = t.entry_id
	WHERE e.word = ? AND t.lang_code = 'en'
	''', ('Hund',))

	print("English:", [row[0] for row in cursor.fetchall()])

	# Example 6: Find words by topic
	cursor.execute('''
	SELECT DISTINCT e.word
	FROM entries e
	JOIN senses s ON e.id = s.entry_id
	JOIN sense_topics st ON s.id = st.sense_id
	JOIN topics t ON st.topic_id = t.id
	WHERE t.topic = 'biology'
	LIMIT 20
	''')

	print("Biology terms:", [row[0] for row in cursor.fetchall()])

	# Example 7: Autocomplete search
	cursor.execute('''
	SELECT DISTINCT word
	FROM entries
	WHERE word LIKE ? AND lang = 'Deutsch'
	ORDER BY word
	LIMIT 10
	''', ('Sch%',))

	print("Words starting with 'Sch':", [row[0] for row in cursor.fetchall()])

	conn.close()
	```

	### Flutter/Dart
	```dart
	import 'package:sqflite/sqflite.dart';
	import 'package:http/http.dart' as http;
	import 'package:path/path.dart';
	import 'package:path_provider/path_provider.dart';
	import 'dart:io';
	import 'package:archive/archive_io.dart';

	class WiktionaryDB {
	static Database? _database;

	Future<Database> get database async {
	if (_database != null) return _database!;
	_database = await initDB();
	return _database!;
	}

	Future<Database> initDB() async {
	final dir = await getApplicationDocumentsDirectory();
	final dbPath = join(dir.path, 'de_wiktionary.db');

	// Download and decompress on first run
	if (!await File(dbPath).exists()) {
	final url = 'https://huggingface.co/datasets/cstr/de-wiktionary-sqlite-normalized/resolve/main/de_wiktionary_normalized.db';

	print('Downloading database...');
	final response = await http.get(Uri.parse(url));

	final gzPath = join(dir.path, 'de_wiktionary.db.gz');
	await File(gzPath).writeAsBytes(response.bodyBytes);

	print('Decompressing...');
	final gzFile = File(gzPath);
	final dbFile = File(dbPath);

	// Decompress gzip
	final bytes = gzFile.readAsBytesSync();
	final archive = GZipDecoder().decodeBytes(bytes);
	await dbFile.writeAsBytes(archive);

	// Clean up
	await gzFile.delete();
	print('Database ready!');
	}

	return await openDatabase(dbPath, version: 1);
	}

	// Get word forms with grammatical tags
	Future<List<Map<String, dynamic>>> getWordForms(String word) async {
	final db = await database;
	return await db.rawQuery('''
	SELECT f.form_text, GROUP_CONCAT(t.tag, ', ') as tags
	FROM entries e
	JOIN forms f ON e.id = f.entry_id
	LEFT JOIN form_tags ft ON f.id = ft.form_id
	LEFT JOIN tags t ON ft.tag_id = t.id
	WHERE e.word = ? AND e.lang = 'Deutsch'
	GROUP BY f.id
	''', [word]);
	}

	// Get synonyms
	Future<List<String>> getSynonyms(String word) async {
	final db = await database;
	final results = await db.rawQuery('''
	SELECT s.synonym_word
	FROM entries e
	JOIN synonyms s ON e.id = s.entry_id
	WHERE e.word = ? AND e.lang = 'Deutsch'
	''', [word]);
	return results.map((r) => r['synonym_word'] as String).toList();
	}

	// Get IPA pronunciation
	Future<List<String>> getIPA(String word) async {
	final db = await database;
	final results = await db.rawQuery('''
	SELECT s.ipa
	FROM entries e
	JOIN sounds s ON e.id = s.entry_id
	WHERE e.word = ? AND s.ipa IS NOT NULL
	''', [word]);
	return results.map((r) => r['ipa'] as String).toList();
	}

	// Get definitions
	Future<List<String>> getDefinitions(String word) async {
	final db = await database;
	final results = await db.rawQuery('''
	SELECT g.gloss_text
	FROM entries e
	JOIN senses se ON e.id = se.entry_id
	JOIN glosses g ON se.id = g.sense_id
	WHERE e.word = ? AND e.lang = 'Deutsch'
	''', [word]);
	return results.map((r) => r['gloss_text'] as String).toList();
	}

	// Autocomplete search
	Future<List<String>> searchWords(String prefix) async {
	final db = await database;
	final results = await db.rawQuery('''
	SELECT DISTINCT word
	FROM entries
	WHERE word LIKE ? AND lang = 'Deutsch'
	ORDER BY word
	LIMIT 20
	''', ['$prefix%']);
	return results.map((r) => r['word'] as String).toList();
	}
	}
	```

	## 🔍 Example Queries

	### Get complete grammatical analysis
	```sql
	SELECT
	e.word,
	f.form_text,
	GROUP_CONCAT(DISTINCT t.tag) as grammatical_tags,
	s.ipa
	FROM entries e
	JOIN forms f ON e.id = f.entry_id
	LEFT JOIN form_tags ft ON f.id = ft.form_id
	LEFT JOIN tags t ON ft.tag_id = t.id
	LEFT JOIN sounds s ON e.id = s.entry_id
	WHERE e.word = 'lieben'
	GROUP BY f.id;
	```

	### Find words by grammatical features
	```sql
	SELECT DISTINCT e.word
	FROM entries e
	JOIN forms f ON e.id = f.entry_id
	JOIN form_tags ft ON f.id = ft.form_id
	JOIN tags t ON ft.tag_id = t.id
	WHERE t.tag = 'irregular' AND e.pos = 'verb'
	LIMIT 100;
	```

	### Get words with semantic relationships
	```sql
	SELECT
	e.word,
	s.synonym_word,
	a.antonym_word
	FROM entries e
	LEFT JOIN synonyms s ON e.id = s.entry_id
	LEFT JOIN antonyms a ON e.id = a.entry_id
	WHERE e.word = 'gut';
	```

	## 📱 Platform Support

	- iOS: ✅ Full support via sqflite
	- Android: ✅ Full support via sqflite
	- Windows: ✅ Via sqflite_common_ffi
	- macOS: ✅ Via sqflite_common_ffi
	- Linux: ✅ Via sqflite_common_ffi
	- Web: ⚠️ Via sql.js (WASM)

	## 🚀 Performance

	Typical query times (modern hardware):
	- Word lookup: < 1ms
	- Get all forms: < 5ms
	- Complex multi-table joins: < 20ms
	- Autocomplete search: < 10ms

	## 🔗 Source

	Original data: [cstr/de-wiktionary-extracted](https://huggingface.co/datasets/cstr/de-wiktionary-extracted)

	## 📜 License

	CC-BY-SA 4.0 (same as source)

	## 🛠️ Technical Details

	- SQLite Version: 3.x compatible
	- Encoding: UTF-8
	- Foreign Keys: Enabled
	- Indexes: 38 indexes for optimal performance
	- Normalization: 3NF with deduplicated tags/topics/categories

	## 📊 Schema Overview
	```
	entries (970K rows)
	├── senses (3.1M) → glosses (3.1M)
	├── forms (6.1M) → form_tags (26M) → tags (185)
	├── sounds (2.3M) → sound_tags
	├── translations (1.1M) → translation_tags
	├── synonyms (162K) → synonym_tags
	├── antonyms
	└── hyphenations (954K)
	```

	## 🤝 Contributing

	Found an issue? Please report it on the source dataset repository.