negspacy
A spaCy pipeline component for negating concepts in text (NegEx).
Decision gist · record as of 2026-08-14
Yes. The package is actively maintained, has no known vulnerabilities, low install friction, permissive licensing, and fills a specific need in NLP pipelines where negation context matters. Best suited for clinical or scientific text processing; general-purpose NLP projects may not need it unless negation handling is a core requirement.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires a spaCy language model to be installed separately (e.g., en_core_web_sm).
- Requires Python >= 3.10.
- Low friction install with a single runtime dependency on spacy.
License · maintenance · safety
permissive license (permissive) — MIT License permits unrestricted use, modification, and distribution with no warranty or liability constraints.
last release 2026-04-20 (116 days) · last repo commit 2026-04-20 · 279 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 121,299 downloads/mo, #11,987 on PyPI
Alternatives
Verify before relying
pip install negspacy
import spacy
from negspacy.negation import Negex
nlp = spacy.load("en_core_web_sm")
nlp.add_pipe("negex")
doc = nlp("She does not like Steve Jobs.")
for e in doc.ents:
print(e.text, e._.negex)- Whether the NegEx algorithm's accuracy or performance characteristics are documented or tested against standard benchmarks.
- Whether the package works with spaCy models beyond en_core_web_sm or if there are known compatibility limitations.
What it is and what it does
negspacy is a spaCy pipeline component that detects negation in text using the NegEx algorithm, originally developed for clinical discharge summaries. It adds a negation attribute to entities and spans, marking whether they are negated in context. The package works by matching negation patterns (preceding negations like 'not', following negations like 'declined', pseudo-negations that are false triggers, and termination phrases like 'but' that reset negation scope) against text around recognized entities.
The package provides three built-in termset configurations: general English (en), clinical English (en_clinical, the default), and a more sensitive clinical variant. Users can customize patterns on the fly, apply negation detection to entity spans or noun chunks, and integrate it into any spaCy 3.0+ pipeline. It's designed for information extraction tasks where distinguishing between asserted and negated concepts matters—particularly in clinical NLP but applicable to any domain where negation context affects meaning.
Use it for
- Extract medical findings from clinical notes while correctly identifying which conditions are negated or ruled out.
- Build clinical decision support systems that distinguish between patient symptoms present versus absent.
- Process scientific literature to identify negated claims or non-findings in research abstracts.
- Improve entity extraction accuracy in domains where negation reverses the semantic meaning of a mention.
- Analyze customer feedback or survey responses to separate complaints from things customers explicitly do not want.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
The package is actively maintained, has no known vulnerabilities, low install friction, permissive licensing, and fills a specific need in NLP pipelines where negation context matters. Best suited for clinical or scientific text processing; general-purpose NLP projects may not need it unless negation handling is a core requirement.
Install
negspacy on PyPI
Before you install
Low friction install with a single runtime dependency on spacy. Actively maintained as of 2026-04-20 with 279 repository stars and recent activity.
Requires a spaCy language model to be installed separately (e.g., en_core_web_sm). Requires Python >= 3.10.
License in practice
MIT License permits unrestricted use, modification, and distribution with no warranty or liability constraints.
Quickstart
pip install negspacy
import spacy
from negspacy.negation import Negex
nlp = spacy.load("en_core_web_sm")
nlp.add_pipe("negex")
doc = nlp("She does not like Steve Jobs.")
for e in doc.ents:
print(e.text, e._.negex)Verify before relying
- Whether the NegEx algorithm's accuracy or performance characteristics are documented or tested against standard benchmarks.
- Whether the package works with spaCy models beyond en_core_web_sm or if there are known compatibility limitations.
Package facts
| License | permissive license permissive |
| Python support | Supports the current Python release >=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 1 packagespacy |
| Maintenance | Actively maintained 116 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 121,299 / month, #11,987 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 5 - Production/StableIntended Audience :: DevelopersIntended Audience :: Science/ResearchLicense :: OSI Approved :: MIT LicenseOperating System :: OS IndependentProgramming Language :: Python :: 3Programming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Topic :: Scientific/EngineeringTyping :: Typed |
Evidence: negspacy-1.1.0-py3-none-any.whl
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