An NLP tool that performs negation resolution on a sentence level. It takes as input a sentence and a target-keyword. It returns True
for affirmed keywords, False
for negated and None
for keywords not found. The tool makes use of Stanford's CoreNLP constituency trees.
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git clone https://github.com/gkotsis/negation-detection
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Download and extract CoreNLP.
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Install stanford_corenlp_pywrapper
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Install through
requirements.txt
:cd negation-detection pip install -r requirements.txt
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Edit
settings.json
. Make sure you keep the leading slashes in the directory names.
##Example
import negation_detection
sentence = "ZZZZ reported no recent periods of low mood, discussed how in the past she made many suicide attempts"
negation_detection.predict(sentence, 'suicide')
George Gkotsis, Sumithra Velupillai, Anika Oellrich, Harry Dean, Maria Liakata and Rina Dutta. Don't Let Notes Be Misunderstood: A Negation Detection Method for Assessing Risk of Suicide in Mental Health Records, Workshop on Computational Linguistics and Clinical Psychology, NAACL 2016.