{"categories":[{"label":"Scientific/Engineering","url":"https://skillfed.io/packages/category/scientific-engineering/7"}],"enrichment":{"capability":"Adds negation detection to spaCy pipelines using the NegEx algorithm, marking whether named entities or spans in text are negated.","skillfed_tags":["negation-detection","clinical-nlp","spacy-component"],"use_cases":["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."],"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.\n\nThe 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\u2014particularly in clinical NLP but applicable to any domain where negation context affects meaning.","worth_installing":"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."},"id":"negspacy","links":{"html":"https://skillfed.io/packages/negspacy","md":"https://skillfed.io/packages/negspacy.md","pypi":"https://pypi.org/project/negspacy/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-04-20","license_spdx":null,"license_treatment":"permissive","name":"negspacy","python_support":"supports_current","summary":"A spaCy pipeline component for negating concepts in text (NegEx)."},"popularity":{"monthly_downloads":121299,"position":11987,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"1.1.0"}