@vaporjawn/esperanto-analyzer

Modern TypeScript morphological analyzer for Esperanto text with comprehensive part-of-speech identification and linguistic analysis capabilities.

Features

• 🔍 Complete Morphological Analysis: Identifies all major Esperanto parts of speech
• 📝 Rich Linguistic Information: Extracts tense, mood, case, number, and other morphological features
• 🎯 High Accuracy: Confidence-based analysis with intelligent precedence rules
• 📊 Sentence-Level Analysis: Analyzes complete sentences with statistical summaries
• 🔧 TypeScript Native: Full type safety with comprehensive type definitions
• 🚀 Modern Package: Dual ESM/CJS support with tree-shaking capabilities
• ✅ Thoroughly Tested: 29 comprehensive tests covering all functionality

Parts of Speech Supported

• Nouns (substantivoj) - with case and number detection
• Verbs (verboj) - with tense, mood, and voice analysis
• Adjectives (adjektivoj) - with case and number agreement
• Adverbs (adverboj) - including derived and correlative forms
• Prepositions (prepozicioj) - complete set recognition
• Conjunctions (konjunkcioj) - coordinating and subordinating
• Pronouns (pronomoj) - personal, correlative, and demonstrative
• Numerals (numeraloj) - cardinal, ordinal, and fractional
• Articles (artikoloj) - definite article recognition
• Interjections (interjekcio) - emotional expressions

Quick Start

Installation

npm install @vaporjawn/esperanto-analyzer

Basic Usage

// CommonJS
const { analyzeWord, analyzeSentence } = require('@vaporjawn/esperanto-analyzer');

// ESM
import { analyzeWord, analyzeSentence } from '@vaporjawn/esperanto-analyzer';

// Analyze a single word
const result = analyzeWord('librojn');
console.log(result.partOfSpeech); // 'Noun'
console.log(result.morphology.isPlural); // true
console.log(result.morphology.isAccusative); // true

// Analyze a sentence
const sentence = analyzeSentence('Mi legas la belan libron');
console.log(sentence.statistics.totalWords); // 5
console.log(sentence.words[0].partOfSpeech); // 'Pronoun'

Individual Component Usage

import {
  MorphologicalAnalyzer,
  MorphologicalSentenceAnalyzer,
  VerbMorphologicalAnalyzer
} from '@vaporjawn/esperanto-analyzer';

// Use specific analyzers directly
const verbAnalyzer = new VerbMorphologicalAnalyzer();
const result = verbAnalyzer.analyze('kuranta');
console.log(result.morphologicalFeatures);
// Output: { tense: 'present', voice: 'active', mood: 'participle' }

Demo

See the complete working example in demo.js:

node demo.js

This demonstrates all major features:

• Word analysis with morphological features
• Sentence analysis with statistics
• Esperanto text validation
• Multiple analysis for ambiguous words
• Part of speech summaries

API Reference

EsperantoAnalyzer

Main analyzer class providing high-level interface.

Methods

• analyzeWord(word: string): AnalysisResult - Analyze single word
• analyzeSentence(sentence: string): SentenceAnalysisResult - Analyze complete sentence
• getMultipleAnalyses(word: string): AnalysisResult[] - Get all possible analyses
• isValidEsperanto(text: string): boolean - Validate Esperanto text
• getPartOfSpeechSummary(text: string): Record<string, number> - Get POS statistics

AnalysisResult

interface AnalysisResult {
  word: string;
  partOfSpeech: PartOfSpeech;
  morphology: MorphologicalFeatures;
  confidence: number;
  alternatives: AnalysisResult[];
}

MorphologicalFeatures

interface MorphologicalFeatures {
  readonly case?: 'nominative' | 'accusative';
  readonly number?: 'singular' | 'plural';
  readonly tense?: 'past' | 'present' | 'future';
  readonly mood?: 'indicative' | 'conditional' | 'imperative' | 'infinitive' | 'participle';
  readonly voice?: 'active' | 'passive';
  readonly degree?: 'positive' | 'comparative' | 'superlative';
  readonly type?: string;
}

Morphological Analysis Details

Confidence System

The analyzer uses a sophisticated confidence calculation system:

• Base confidence: Calculated from morphological feature matches
• High-confidence rules: Special cases for unambiguous forms
• Precedence system: Resolves conflicts between multiple possible analyses

Feature Detection

Each analyzer specializes in detecting specific morphological features:

• Case marking: Automatic detection of accusative (-n) and nominative forms
• Number marking: Plural detection with confidence adjustment
• Verbal features: Comprehensive tense, mood, and voice analysis
• Adjectival agreement: Case and number agreement with nouns

Development

Building

npm run build

This creates three output formats:

• dist/types/ - TypeScript type definitions
• dist/esm/ - ES modules for modern bundlers
• dist/cjs/ - CommonJS for Node.js compatibility

Testing

npm test              # Run all tests
npm run test:watch    # Watch mode
npm run test:coverage # Coverage report

Code Quality

npm run lint          # Check code style
npm run lint:fix      # Fix auto-fixable issues
npm run format        # Format code with Prettier
npm run typecheck     # Verify TypeScript types

Migration from Python Version

This TypeScript version maintains API compatibility with enhanced features:

Key Improvements

• Type Safety: Full TypeScript support with comprehensive type definitions
• Modern Package: Dual ESM/CJS support with proper tree-shaking
• Enhanced Testing: 29 comprehensive tests with edge case coverage
• Better Performance: Optimized algorithms with confidence-based selection
• Rich Morphology: Expanded morphological feature detection

Breaking Changes

• Package name changed to @vaporjawn/esperanto-analyzer
• Constructor patterns updated for TypeScript classes
• Return types now include comprehensive type information

Contributing

1. Fork the repository
2. Create a feature branch: git checkout -b feature-name
3. Make your changes with tests
4. Run the test suite: npm test
5. Submit a pull request

License

MIT License - see LICENSE file for details.

Acknowledgments

Based on the original Python Esperanto analyzer with significant enhancements for modern TypeScript development. Special thanks to the Esperanto community for linguistic guidance and validation.

Saluton al ĉiuj Esperantistoj! 🌍✨