def checkForInverterWordInPreceedingSentence(self, sentence, argExtractor):
#TODO: Work on an NLTK contractions aclass to filer out words like not etc
symtomStatements = [
'side-effects', 'side effects', 'symptoms', 'symptom'
]
# Extract the words preceeding the symptomStatement keyword
preceedingSentence = ''
sideEffectStatus = ''
listOfContractions = argExtractor.getListOfContractions()
expandedSentence = messageCleaner.replaceWordContractions(
sentence, listOfContractions)
for symptomStatement in symtomStatements:
indexOfSymptomKeyWord = expandedSentence.find(symptomStatement)
if indexOfSymptomKeyWord == -1:
continue
# We pull out the preceeeding sentence. We have a -1 here in the final index range so that we can remove the space before the key symptom word
preceedingSentence = expandedSentence[0:(indexOfSymptomKeyWord -
1)]
break
# This means we could not find the key word from the side effects list
if preceedingSentence == '':
return (False, sideEffectStatus)
try:
taggedSentence = naturalLanguageWhiz.tag(preceedingSentence)
if len(taggedSentence) <= 0:
return (False, sideEffectStatus)
except:
logger.exception('Error when running checkForMentionOfNoSymptoms')
return (False, sideEffectStatus)
result = argExtractor.checkIfInverterWordInSentence(taggedSentence)
if result == True:
sideEffectStatus = 'Possibly no side effects'
return (True, sideEffectStatus)
else:
sideEffectStatus = 'Side effects Present - because no preceeding inverterword'
return (False, sideEffectStatus)
def checkForInverterWordInPreceedingSentence(self, sentence, argExtractor):
#TODO: Work on an NLTK contractions aclass to filer out words like not etc
symtomStatements = ['side-effects', 'side effects', 'symptoms', 'symptom']
# Extract the words preceeding the symptomStatement keyword
preceedingSentence = ''
sideEffectStatus = ''
listOfContractions = argExtractor.getListOfContractions()
expandedSentence = messageCleaner.replaceWordContractions(sentence, listOfContractions)
for symptomStatement in symtomStatements:
indexOfSymptomKeyWord = expandedSentence.find(symptomStatement)
if indexOfSymptomKeyWord == -1:
continue
# We pull out the preceeeding sentence. We have a -1 here in the final index range so that we can remove the space before the key symptom word
preceedingSentence = expandedSentence[0:(indexOfSymptomKeyWord - 1)]
break
# This means we could not find the key word from the side effects list
if preceedingSentence == '':
return (False, sideEffectStatus)
try:
taggedSentence = naturalLanguageWhiz.tag(preceedingSentence)
if len(taggedSentence) <= 0:
return (False, sideEffectStatus)
except:
logger.exception('Error when running checkForMentionOfNoSymptoms')
return (False, sideEffectStatus)
result = argExtractor.checkIfInverterWordInSentence(taggedSentence)
if result == True:
sideEffectStatus = 'Possibly no side effects'
return (True, sideEffectStatus)
else:
sideEffectStatus = 'Side effects Present - because no preceeding inverterword'
return (False, sideEffectStatus)
def checkForMentionOfNoSymptoms(self, sentence, argExtractor):
symtomStatements = [
'side-effects', 'side effects', 'symptoms', 'symptom'
]
# Extract the words preceeding the symptomStatement keyword
preceedingSentence = ''
symptomMentioned = ''
for symptomStatement in symtomStatements:
indexOfSymptomKeyWord = sentence.find(symptomStatement)
if indexOfSymptomKeyWord == -1:
continue
# We pull out the preceeeding sentence. We have a -1 here in the final index range so that we can remove the space before the key symptom word
preceedingSentence = sentence[0:(indexOfSymptomKeyWord - 1)]
break
# This means we could not find the key word from the side effects list
if preceedingSentence == '':
return (False, symptomMentioned)
try:
taggedSentence = naturalLanguageWhiz.tag(preceedingSentence)
if len(taggedSentence) <= 0:
return (False, symptomMentioned)
except:
logger.exception('Error when running checkForMentionOfNoSymptoms')
return (False, symptomMentioned)
result = argExtractor.checkIfInverterWordEndOfSentence(taggedSentence)
if result == True:
symptomMentioned = 'No Side Effects'
return (True, symptomMentioned)
else:
symptomMentioned = 'Side effects Present - because of no direct inverter word before '
return (False, symptomMentioned)
def checkForMentionOfNoSymptoms(self, sentence, argExtractor):
symtomStatements = ['side-effects', 'side effects', 'symptoms', 'symptom']
# Extract the words preceeding the symptomStatement keyword
preceedingSentence = ''
symptomMentioned = ''
for symptomStatement in symtomStatements:
indexOfSymptomKeyWord = sentence.find(symptomStatement)
if indexOfSymptomKeyWord == -1:
continue
# We pull out the preceeeding sentence. We have a -1 here in the final index range so that we can remove the space before the key symptom word
preceedingSentence = sentence[0:(indexOfSymptomKeyWord - 1)]
break
# This means we could not find the key word from the side effects list
if preceedingSentence == '':
return (False, symptomMentioned)
try:
taggedSentence = naturalLanguageWhiz.tag(preceedingSentence)
if len(taggedSentence) <= 0:
return (False, symptomMentioned)
except:
logger.exception('Error when running checkForMentionOfNoSymptoms')
return (False, symptomMentioned)
result = argExtractor.checkIfInverterWordEndOfSentence(taggedSentence)
if result == True:
symptomMentioned = 'No Side Effects'
return (True, symptomMentioned)
else:
symptomMentioned = 'Side effects Present - because of no direct inverter word before '
return (False, symptomMentioned)
