negspacy 0.1.4

A spaCy pipeline object for negation.

negspacy: negation for spaCy

spaCy pipeline object for negating concepts in text. Based on the NegEx algorithm.

NegEx - A Simple Algorithm for Identifying Negated Findings and Diseasesin Discharge Summaries Chapman, Bridewell, Hanbury, Cooper, Buchanan

Installation and usage

Install the library.

pip install negspacy

Import library and spaCy.

import spacy
from negspacy.negation import Negex

Load spacy language model. Add negspacy pipeline object. Filtering on entity types is optional.

nlp = spacy.load("en_core_web_sm")
negex = Negex(nlp, ent_types=["PERSON","ORG"])
nlp.add_pipe(negex, last=True)

View negations.

doc = nlp("She does not like Steve Jobs but likes Apple products.")

for e in doc.ents:
	print(e.text, e._.negex)

Steve Jobs True
Apple False

Consider pairing with scispacy to find UMLS concepts in text and process negations.

NegEx Patterns

• psuedo_negations - phrases that are false triggers, ambiguous negations, or double negatives
• preceding_negations - negation phrases that preceed an entity
• following_negations - negation phrases that follow an entity
• termination - phrases that cut a sentence in parts, for purposes of negation detection (.e.g., "but")

Use own patterns or view patterns in use

Use own patterns

nlp = spacy.load("en_core_web_sm")
negex = Negex(nlp, termination=["but", "however", "nevertheless", "except"])

View patterns in use

patterns_dict = negex.get_patterns

Contributing

contributing

Authors

• Jeno Pizarro

License

license

API Documentation

Docs