wordnet-lookup 1.3.4

Static Dictionaries for Rapid Wordnet Lookups

WordNet Lookup

Is this token a word? O(1) answer. No setup. No dependencies.

A simple question deserves a simple answer. This library gives you instant yes/no validation against 88,000 common English words from the Princeton WordNet lexicon - plus morphological suffix extraction.

Quick Start

pip install wordnet-lookup

from wordnet_lookup import is_wordnet_term, get_suffixes, get_inflections, get_morphology

# Word existence - O(1), no I/O
is_wordnet_term('alpha')        # True
is_wordnet_term('waddling')     # True
is_wordnet_term('myxovirus')    # True
is_wordnet_term('nonexistent')  # False

# Case-insensitive, whitespace-tolerant
is_wordnet_term('ALPHA')        # True
is_wordnet_term(' alpha ')      # True

# Plurals handled automatically
is_wordnet_term('computers')    # True

# Morphological suffix extraction
get_suffixes('happiness')       # ['ness']
get_suffixes('beautifully')     # ['ful', 'ly']
get_suffixes('nationalized')    # ['al', 'ize', 'ed']
get_suffixes('cat')             # []   - in WordNet, no derivational suffixes
get_suffixes('xyz123')          # None - not in WordNet

# Inflectional suffix detection (runtime, not pre-computed)
get_inflections('cats')         # ['s']
get_inflections('running')      # ['ing']
get_inflections('walked')       # ['ed']
get_inflections('fastest')      # ['est']
get_inflections('cat')          # []   - base form, no inflection
get_inflections('xyz123')       # None - not in WordNet

# Combined morphological analysis
m = get_morphology('beautifully')
m.derivational  # ['ful', 'ly']
m.inflectional  # []

m = get_morphology('cats')
m.derivational  # []
m.inflectional  # ['s']

Features

• Zero Dependencies - Pure Python, no external packages
• Zero I/O - No filesystem access, no database queries
• Zero Setup - No corpus downloads or configuration
• Microsecond Lookups - O(1) hash-based access
• Smart Plurals - Automatically checks singular forms
• Unicode Normalization - Accented forms (e.g. naïve, café) resolved to ASCII
• Suffix Extraction - get_suffixes() returns derivational suffixes in order, or None if the word isn't in WordNet
• Inflectional Detection - get_inflections() detects -s, -es, -ing, -ed, -est at runtime with allomorphic stem restoration
• Combined Morphology - get_morphology() returns a Morphology dataclass with both derivational and inflectional suffix lists

When to Use This

• Tokenization filtering - Keep real words, discard garbage
• Input validation - Reject nonsense in user input
• NLP preprocessing - Filter candidates before expensive operations
• Morphological analysis - Identify suffix chains for stemming pipelines
• Data cleaning - Identify malformed or corrupted text

What This Doesn't Do

• No definitions, synonyms, or semantic relationships (use spaCy for that)
• No slang, proper nouns, or recent coinages (WordNet is from 2006)
• No spell-checking or suggestions (just yes/no)
• No hyphenated compounds or multi-word phrases

Documentation

See API Documentation and Implementation Notes for full details.

Development

git clone https://github.com/craigtrim/wordnet-lookup.git
cd wordnet-lookup
make all      # Full build pipeline

License

Dual-licensed: MIT (software) + Princeton WordNet License (data). See LICENSE.

WordNet 3.0 Copyright 2006 by Princeton University. All rights reserved.

See Also

• bnc-lookup - O(1) lookup using the British National Corpus
• morphroot - Suffix extraction pipeline that feeds this library

Links

• Repository: github.com/craigtrim/wordnet-lookup
• PyPI: pypi.org/project/wordnet-lookup
• WordNet: wordnet.princeton.edu