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SpaCy

spaCy (/speɪˈsiː/ spay-SEE) is an open-source software library for advanced natural language processing, written in the programming languages Python and Cython. The library is published under the MIT license and its main developers are Matthew Honnibal and Ines Montani, the founders of the software company Explosion.

History & Companies

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Research this topic

Explore the main themes, entities and connections around SpaCy. Start with the topic map, then use the sections below for research and deeper semantic analysis.

Explore this topic

Start with a few of the strongest sections from the source topic. These are research directions, not a list of keywords you must use.

Key facts & relationships

High-confidence facts extracted from structured source data. Use them as anchors for further research.

Developers
Explosion AI, various
License
MIT License
Operating system
Linux, Windows, macOS, OS X
Original author
Matthew Honnibal
Platform
Cross-platform
Release
February 2015; 11 years ago (2015-02)

Topics to explore

Browse the full topic structure. Each item opens a new analysis centered on that subject.

Overview

History

Main features

Extensions and visualizers

Advanced semantic analysis

Deeper signals for content research, entity SEO and topical coverage. The plain-language headings explain what each technical view is useful for.

Map overview Semantic statistics

SpaCy

Nodes42
Edges41
Triples35
Avg. degree1.95
Density0.047619
Components1

How this topic connects Entity context

See the strongest relationship patterns around the current topic before diving into the raw triples.

SpaCy

Top relations

related to Extensions and visualizers · 7
SpaCy → An, CPU, CSS, JavaScript, SVG, Thinc, Word2vec
related to External links · 2
SpaCy → Official, Spacy Library
Developers · 1
SpaCy → Explosion AI, various
License · 1
SpaCy → MIT License
Operating system · 1
SpaCy → Linux, Windows, macOS, OS X
Original author · 1
SpaCy → Matthew Honnibal
Platform · 1
SpaCy → Cross-platform
Release · 1
SpaCy → February 2015; 11 years ago (2015-02)
Repository · 1
SpaCy → github.com/explosion/spaCy
Stable release · 1
SpaCy → 3.8.4 / 14 January 2025; 19 months ago (14 January 2025)

Important terminology Word statistics

Use these terms to understand the vocabulary surrounding the topic, not as a checklist for keyword stuffing.

Important terminology

models library languages also open-source software entity processing python support custom statistical thinc neural network dependency natural language cython version

Entity relationships Subject–Predicate–Object triples

SubjectPredicateObjectConfidenceSrc
SpaCyDevelopersExplosion AI, various1.00infobox
SpaCyLicenseMIT License1.00infobox
SpaCyOperating systemLinux, Windows, macOS, OS X1.00infobox
SpaCyOriginal authorMatthew Honnibal1.00infobox
SpaCyPlatformCross-platform1.00infobox
SpaCyReleaseFebruary 2015; 11 years ago (2015-02)1.00infobox
SpaCyRepositorygithub.com/explosion/spaCy1.00infobox
SpaCyStable release3.8.4 / 14 January 2025; 19 months ago (14 January 2025)1.00infobox
SpaCyTypeNatural language processing1.00infobox
SpaCyWebsitespacy.io1.00infobox
SpaCyWritten inPython, Cython1.00infobox
Named entity recognitioninstance ofsupport for over 65 languagesBuilt-in support for trainable pipeline components0.80text

Related concept clusters Concept neighborhoods

These clusters group vocabulary that occurs around closely connected concepts in the source material.

    Connections between topic areas Semantic bridges

    Bridges can reveal useful research angles that are easy to miss in a flat list of related terms.

    Min side: 3
    For writers, content strategists, SEOs, marketers and creators — from quick topic research to advanced semantic analysis.