wn
Wordnet interface library
Decision gist · record as of 2026-08-14
Yes. Wn is actively maintained, has no known vulnerabilities, installs with low friction, and offers a clean modern interface to wordnet data with strong multilingual support. It's a solid choice for NLP and linguistic tasks, especially if you need multiple languages or are migrating from NLTK. The only prerequisite is downloading wordnet data separately, which is straightforward.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.10 or later.
- Wordnet data must be downloaded separately via `python -m wn download` before querying.
- Low install friction: pure Python wheel with only two lightweight runtime dependencies (httpx and tomli).
License · maintenance · safety
permissive license (permissive) — MIT License permits unrestricted use, modification, and redistribution for commercial and private projects with minimal obligations—only attribution and license inclusion required.
last release 2026-08-14 (0 days) · last repo commit 2026-08-14 · 299 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 157,397 downloads/mo, #10,757 on PyPI
Alternatives
Verify before relying
pip install wn
python -m wn download oewn:2025+
import wn
en = wn.Wordnet('oewn:2025+')
synsets = en.synsets('win', pos='v')
print(synsets[0].definition())- Performance characteristics and query speed on large wordnet datasets compared to alternatives
- Memory footprint of the SQL-based backend for typical use cases
- Completeness and accuracy of available wordnets across supported languages
What it is and what it does
Wn is a Python interface to wordnet databases—structured lexical resources that organize words into synonym sets (synsets) with definitions, part-of-speech tags, and semantic relationships. It provides a modern alternative to NLTK's wordnet module, with a SQL-backed database for fast queries and first-class support for multiple languages and interlingual lookups via the Collaborative Interlingual Index. The library lets you download wordnets from a curated index (similar to a package manager), query them for definitions and synonyms, explore taxonomies, compute word similarity, and perform lemmatization.
You start by downloading a wordnet (e.g., Open English WordNet 2025+) via the command line, then import the library and create a Wordnet object to query. It handles both English wordnets (with multiple historical versions for compatibility) and non-English wordnets in languages including German, Portuguese, Japanese, Spanish, and many others. The library supports the WN-LMF 1.4 format, including word pronunciations and custom lexicon extensions.
Use it for
- Build semantic similarity or word-sense disambiguation features for NLP applications by querying synset relationships and definitions.
- Migrate from NLTK's wordnet module to a faster, more actively maintained alternative with better multilingual support.
- Perform cross-lingual semantic lookups using the Collaborative Interlingual Index to find equivalent concepts across languages.
- Extract lemmatized forms and morphological variants for text preprocessing in linguistic research or information retrieval.
- Explore word taxonomies and hypernym/hyponym relationships for knowledge graph construction or ontology building.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
Wn is actively maintained, has no known vulnerabilities, installs with low friction, and offers a clean modern interface to wordnet data with strong multilingual support. It's a solid choice for NLP and linguistic tasks, especially if you need multiple languages or are migrating from NLTK. The only prerequisite is downloading wordnet data separately, which is straightforward.
Install
wn on PyPI
Before you install
Low install friction: pure Python wheel with only two lightweight runtime dependencies (httpx and tomli). Active maintenance with a recent release and no known vulnerabilities.
Requires Python 3.10 or later. Wordnet data must be downloaded separately via `python -m wn download` before querying.
License in practice
MIT License permits unrestricted use, modification, and redistribution for commercial and private projects with minimal obligations—only attribution and license inclusion required.
Quickstart
pip install wn
python -m wn download oewn:2025+
import wn
en = wn.Wordnet('oewn:2025+')
synsets = en.synsets('win', pos='v')
print(synsets[0].definition())Verify before relying
- Performance characteristics and query speed on large wordnet datasets compared to alternatives
- Memory footprint of the SQL-based backend for typical use cases
- Completeness and accuracy of available wordnets across supported languages
Package facts
| License | permissive license permissive |
| Python support | Supports the current Python release >=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 2 packageshttpxtomli |
| Maintenance | Actively maintained 0 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 157,397 / month, #10,757 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 4 - BetaEnvironment :: ConsoleIntended Audience :: DevelopersIntended Audience :: Information TechnologyIntended Audience :: Science/ResearchLicense :: OSI Approved :: MIT LicenseProgramming Language :: Python :: 3Programming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14Topic :: Scientific/Engineering :: Information AnalysisTopic :: Software Development :: Libraries :: Python ModulesTopic :: Text Processing :: Linguistic |
Evidence: wn-1.1.1-py3-none-any.whl
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