def extract(self, cas: Cas) -> (str, float):
studentView = cas.get_view(FeatureExtractor.STUDENT_ANSWER_VIEW)
variety = 0.0
for al in AlignmentLabel:
variety += self.get_perc_of_mapping_type(studentView, al)
return ("Variety", variety)
def extract(self, cas: Cas) -> (str, float):
studentView = cas.get_view(FeatureExtractor.STUDENT_ANSWER_VIEW)
answer = next(studentView.select(FeatureExtractor.ANSWER_TYPE))
score = answer.contentScore
if score in Outcome.LABEL2INT:
return ("Outcome", Outcome.LABEL2INT[score])
else:
try:
outcome = float(score)
except ValueError:
outcome = float('nan')
return ("Outcome", outcome)
def extract(self, cas: Cas) -> (str, float):
view = cas.get_view(self.view_name)
dep_matches = len(list(view.select(TripleOverlap.DEP_MAPPING_TYPE)))
dep_rels = 0
for d in view.select(FeatureExtractor.DEPENDENCY_TYPE):
if d.DependencyType in self.english_arg_rels:
dep_rels += 1
ret = -1.0
if not dep_rels:
ret = 0.0
else:
ret = dep_matches / dep_rels
return (self.view_name + "-Triple-Overlap", ret)
def extract(self, cas: Cas) -> (str, float):
view = cas.get_view(self.view_name)
matched_ann = 0
all_ann = 0
for a in view.select(self.ann_type):
all_ann += 1
mappable = self.get_mappable_ann(view, a)
if mappable.match:
matched_ann += 1
ret = -1.0
if not all_ann:
ret = 0.0
else:
ret = matched_ann / all_ann
return (self.view_name + "-" + uima.simple_type_name(self.ann_type) +
"-Overlap", ret)
def extract(self, cas: Cas) -> (str, float):
studentView = cas.get_view(FeatureExtractor.STUDENT_ANSWER_VIEW)
return (self.alignment.name + "-Match",
self.get_perc_of_mapping_type(studentView, self.alignment))
def extract(self, cas: Cas) -> (str, float):
studentView = cas.get_view(FeatureExtractor.STUDENT_ANSWER_VIEW)
answer = next(studentView.select(FeatureExtractor.ANSWER_TYPE))
return ("Diagnosis", int(answer.contentDiagnosis))
def _get_indexed_feature_structures(cas: Cas) -> Iterable[FeatureStructure]:
feature_structures = []
for sofa in cas.sofas:
view = cas.get_view(sofa.sofaID)
feature_structures.extend(view.select_all())
return feature_structures
