[{'role': 'system', 'content': "You are an expert in machine learning and your task is to classify the code snippets into categories from the provided list of categories. List of categories: ['helper_functions', 'load_data', 'data_exploration', 'data_preprocessing', 'evaluation', 'modelling', 'prediction', 'result_visualization', 'save_results', 'comment_only']"}, {'role': 'user', 'content': 'Identify to which category the provided code belongs and assign the code snippet to at least 1 but up to 5 categories based on the probabilities, ignore if the probability of the category is negligible. Strictly provide your response as a list. Avoid providing any additional information, commentary, or personal opinions.\\nPython Code:# This Python 3 environment comes with many helpful analytics libraries installed\n# It is defined by the kaggle/python docker image: https://github.com/kaggle/docker-python\n# For example, here\'s several helpful packages to load in \n\nimport numpy as np # linear algebra\nimport pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n\n# Input data files are available in the "../input/" directory.\n# For example, running this (by clicking run or pressing Shift+Enter) will list the files in the input directory\n\nimport os\nimport re\nprint(os.listdir("../input"))\n\nimport spacy\nimport networkx as nx\n\nimport zipfile\n\nsample_submission = pd.read_csv("../input/gendered-pronoun-resolution/sample_submission_stage_1.csv")\nfinal_test = pd.read_csv("../input/gendered-pronoun-resolution/test_stage_2.tsv", sep = "\\\\t")\nnlp = spacy.load(\'en_core_web_sm\')\ndep = ["ACL", "ACOMP", "ADVCL", "ADVMOD", "AGENT", "AMOD", "APPOS", "ATTR", "AUX", "AUXPASS",\n       "CASE", "CC", "CCOMP", "COMPOUND", "CONJ", "CSUBJ", "CSUBJPASS", "DATIVE", "DEP", "DET", "DOBJ"\n     , "EXPL", "INTJ", "MARK", "META", "NEG", "NOUNMOD", "NPMOD", "NSUBJ", "NSUBJPASS", "NUMMOD"\n     , "OPRD", "PARATAXIS", "PCOMP", "POBJ", "POSS", "PRECONJ", "PREDET", "PREP", "PRT", "PUNCT", "QUANTMOD",\n       "RELCL", "ROOT", "XCOMP", "COMPLM","INFMOD","PARTMOD","HMOD","HYPH","IOBJ","NUM",\n       "NUMBER","NMOD","NN","NPADVMOD","POSSESSIVE","RCMOD","SUBTOK"]\n\n# Any results you write to the current directory are saved as output.'}, {'role': 'assistant', 'content': "['helper_functions']"}]