| from cassis import * |
| import csv |
| from nltk.tokenize import word_tokenize |
|
|
| sentence_id = 0 |
| number = 0 |
|
|
| max_length = 0 |
| min_length = 10000 |
| sum_length = 0 |
| count = 0 |
|
|
| annotator_1 = [['Annotator_1','Annotated_part_1','Final_Dataset_tsv'],['Annotator_1','Annotated_part_2','ratemy_professor_data_from_sorted_list_shuffle_1']] |
| annotator_2=[['Annotator_3','Annotated_part_6','Final_Dataset_tsv']] |
| annotator_3 = [['Annotator_2','Annotated_part_3','Final_Dataset_tsv'],['Annotator_2','Annotated_part_4','ratemy_professor_data_from_sorted_list_shuffle_1'],['Annotator_2','Annotated_part_5','additional_100_of_rate_my_proffesor']] |
| annotators = [annotator_1,annotator_2,annotator_3] |
| path_for_folder = "./Annotated Student Feedback Data/" |
|
|
| with open(path_for_folder+'Annotator_3/Annotated_part_6/TypeSystem.xml', 'rb') as f: |
| typesystem_tmp = load_typesystem(f) |
| for annotator in annotators: |
| for path_for_data in annotator: |
|
|
|
|
| with open('/content/drive/Shareddrives/FYP/Annotated Data/'+path_for_data[0]+'/'+path_for_data[1]+'/'+path_for_data[2]+'.xmi', 'rb') as f: |
| doc_tmp = load_cas_from_xmi(f, typesystem=typesystem_tmp) |
|
|
| data = doc_tmp.sofa_string |
| for (_, sentence) in enumerate(doc_tmp.select('webanno.custom.'+"Document_levelopinion")): |
| if sentence.Document_levelopinion != None: |
| count +=1 |
| length = len(word_tokenize(sentence.get_covered_text())) |
| sum_length += (length) |
| if length > max_length: |
| max_length = length |
| if length < min_length: |
| min_length = length |
| print("max = ",max_length) |
| print("min = ",min_length) |
| print("sum = ",sum_length/count) |
