def post(self):
params = {x: request.form[x] for x in request.form}
StandardNLP.process(params)
FeatureExtractor.process(params)
Classifier.process(params)
Executor.process(params)
return params
def post(self):
params = {x: request.form[x] for x in request.form}
StandardNLP.process(params)
FeatureExtractor.process(params)
Classifier.process(params)
Executor.process(params)
return params
def get_confs_kws(query, services):
params = {'query': query}
StandardNLP.process(params)
keywords = find_keywords(params['features']['tokens'])
confidences = {}
for name, heuristic in services.iteritems():
confidences[name] = heuristic.run_heuristic(keywords)
return confidences, keywords + ['BIAS']
def process(cls, params):
Validator.process(params)
if 'error' in params:
cls.LOGGER.error(message=params['error'])
abort(404, message=params['error'])
StandardNLP.process(params)
FeatureExtractor.process(params)
Classifier.process(params)
Executor.process(params)
Logger.process(params)
Sanitizer.process(params)
def post(self):
params = {x: request.form[x] for x in request.form}
StandardNLP.process(params)
return find_nouns(params['features']['pos'])[1]
def post(self):
params = {x: request.form[x] for x in request.form}
StandardNLP.process(params)
return classify_question(params['features']['tokens'])
def post(self):
params = {x: request.form[x] for x in request.form}
StandardNLP.process(params)
return is_question(params["features"]["tokens"])
def test_nouns():
for test in test_cases:
sent, tokens, exp_features = test
processed = StandardNLP.process(sent)
features = FeatureExtractor.extract_features(processed)
assert features['nouns'] == exp_features['nouns']
def test_nouns():
for test in test_cases:
sent, tokens, exp_features = test
processed = StandardNLP.process(sent)
features = FeatureExtractor.extract_features(processed)
assert features['nouns'] == exp_features['nouns']
def test_pre_processing():
for test in test_cases:
sent, tokens, exp_features = test
processed = StandardNLP.process(sent)
assert processed['pos'] == tokens
def post(self):
params = {x: request.form[x] for x in request.form}
StandardNLP.process(params)
return get_tense(params['features']['pos'])
def post(self):
params = {x: request.form[x] for x in request.form}
StandardNLP.process(params)
return get_tense(params['features']['pos'])
def post(self):
params = {x: request.form[x] for x in request.form}
StandardNLP.process(params)
return find_keywords(params['features']['tokens'])
def post(self):
params = {x: request.form[x] for x in request.form}
StandardNLP.process(params)
return find_keywords(params['features']['tokens'])
def test_question_type():
for test in test_cases:
sent, tokens, exp_features = test
processed = StandardNLP.process(sent)
features = FeatureExtractor.extract_features(processed)
assert features['questionType'] == exp_features['questionType']
def test_question_type():
for test in test_cases:
sent, tokens, exp_features = test
processed = StandardNLP.process(sent)
features = FeatureExtractor.extract_features(processed)
assert features['questionType'] == exp_features['questionType']
def post(self):
params = {x: request.form[x] for x in request.form}
StandardNLP.process(params)
return classify_question(params['features']['tokens'])
def test_pre_processing():
for test in test_cases:
sent, tokens, exp_features = test
processed = StandardNLP.process(sent)
assert processed['pos'] == tokens
