def extractPhrasePaireFeature(phrasedir):
for lec in annotation.Lectures:
path = phrasedir + str(lec)+ '/'
fio.NewPath(path)
for prompt in ['q1', 'q2']:
prefix = os.path.join(path, '%s.%s.'%(prompt, method))
filename = path + prompt + sim_exe
print filename
featureset = []
feature_extractor = Similarity(prefix)
phrasefile = os.path.join(path, "%s.%s.key"%(prompt, method))
phrases = fio.LoadList(phrasefile)
for p1 in phrases:
for p2 in phrases:
featureset.append((feature_extractor.get_features(p1, p2), 0.0, {'p1':p1, 'p2':p2}))
fio.SaveDict2Json(featureset, filename)
feature_extractor.save()
def extractPhrasePaireFeature(phrasedir):
for lec in annotation.Lectures:
path = phrasedir + str(lec) + '/'
fio.NewPath(path)
for prompt in ['q1', 'q2']:
prefix = os.path.join(path, '%s.%s.' % (prompt, method))
filename = path + prompt + sim_exe
print filename
featureset = []
feature_extractor = Similarity(prefix)
phrasefile = os.path.join(path, "%s.%s.key" % (prompt, method))
phrases = fio.LoadList(phrasefile)
for p1 in phrases:
for p2 in phrases:
featureset.append(
(feature_extractor.get_features(p1, p2), 0.0, {
'p1': p1,
'p2': p2
}))
fio.SaveDict2Json(featureset, filename)
feature_extractor.save()
def extractPhrasePaireFromAnnotation(phrasedir, annotators, id):
for doc, lec, annotator in annotation.generate_all_files(
annotation.datadir + 'json/',
'.json',
anotators=annotators,
lectures=annotation.Lectures):
print doc
#load task
task = annotation.Task()
task.loadjson(doc)
path = phrasedir + str(lec) + '/'
fio.NewPath(path)
for prompt in ['q1', 'q2']:
prefix = os.path.join(path, '%s.%s.' % (prompt, method))
filename = path + prompt + sim_exe
print filename
featureset = []
feature_extractor = Similarity(prefix)
phrase_annotation = task.get_phrase_annotation(prompt)
#positive examples
for rank1 in sorted(phrase_annotation):
for rank2 in sorted(phrase_annotation):
if rank1 == rank2:
score = 1.0
else:
score = 0.0
phrases1 = phrase_annotation[rank1]
phrases2 = phrase_annotation[rank2]
for phrasedict1 in phrases1:
p1 = phrasedict1['phrase'].lower().strip()
for phrasedict2 in phrases2:
p2 = phrasedict2['phrase'].lower().strip()
featureset.append(
(feature_extractor.get_features(p1,
p2), score, {
'p1': p1,
'p2': p2
}))
fio.SaveDict2Json(featureset, filename)
feature_extractor.save()
def extractPhrasePaireFromAnnotation(phrasedir, annotators, id):
for doc, lec, annotator in annotation.generate_all_files(annotation.datadir + 'json/', '.json', anotators = annotators, lectures=annotation.Lectures):
print doc
#load task
task = annotation.Task()
task.loadjson(doc)
path = phrasedir + str(lec)+ '/'
fio.NewPath(path)
for prompt in ['q1', 'q2']:
prefix = os.path.join(path, '%s.%s.'%(prompt, method))
filename = path + prompt + sim_exe
print filename
featureset = []
feature_extractor = Similarity(prefix)
phrase_annotation = task.get_phrase_annotation(prompt)
#positive examples
for rank1 in sorted(phrase_annotation):
for rank2 in sorted(phrase_annotation):
if rank1 == rank2:
score = 1.0
else:
score = 0.0
phrases1 = phrase_annotation[rank1]
phrases2 = phrase_annotation[rank2]
for phrasedict1 in phrases1:
p1 = phrasedict1['phrase'].lower().strip()
for phrasedict2 in phrases2:
p2 = phrasedict2['phrase'].lower().strip()
featureset.append((feature_extractor.get_features(p1, p2), score, {'p1':p1, 'p2':p2}))
fio.SaveDict2Json(featureset, filename)
feature_extractor.save()
