from __future__ import print_function from __future__ import print_function import sys from polarity_classifier import PolarityClassifier from KafNafParserPy import KafNafParser if __name__ == '__main__': files = [] fd = open('nl.list.test') for line in fd: files.append(line.strip()) fd.close() my_polarity_classifier = PolarityClassifier('nl') my_polarity_classifier.load_models(sys.argv[1]) OK = WR = 1 for example_file in files: this_obj = KafNafParser(example_file) my_polarity_classifier.classify_kaf_naf_object(this_obj) this_obj.dump() break GOLD = {} list_ids_term_ids = [] for opinion in this_obj.get_opinions(): op_exp = opinion.get_expression()
for e, t, h in final_triples: print(' ==>', file=sys.stderr) print(' Expression:', e.to_line(), file=sys.stderr) if t is None: print(' Target: NONE', file=sys.stderr) else: print(' Target:', t.to_line(), file=sys.stderr) if h is None: print(' Holder: NONE', file=sys.stderr) else: print(' Holder:', h.to_line(), file=sys.stderr) #Remove feature_file feature_file #Remove also the target file target_features_file os.remove(feature_file) os.remove(target_features_file) os.remove(holder_features_file) ## CREATE THE KAF/NAF OPINIONS add_opinions(final_triples, kaf_naf_obj) if args.polarity: my_polarity_classifier = PolarityClassifier(language) my_polarity_classifier.load_models( os.path.join(__here__, 'polarity_models', language)) my_polarity_classifier.classify_kaf_naf_object(kaf_naf_obj) kaf_naf_obj.dump()