[{'role': 'system', 'content': "You are an expert in machine learning and your task is to classify code snippets into one of the following categories: ['helper_functions', 'load_data', 'data_exploration', 'data_preprocessing', 'evaluation', 'modelling', 'prediction', 'result_visualization', 'save_results', 'comment_only']."}, {'role': 'user', 'content': "Identify the single most appropriate category to which the provided code belongs. Provide your response as a single category label without any additional information, commentary, or personal opinions.\\nPython Code:def get_coref(row):\n    coref = None\n    \n    nlpr = nlp(row['Text'])\n    \n    # dunno if more direct way to get token from text offset\n    for tok in nlpr.doc:\n        if tok.idx == row['Pronoun-offset']:\n            # model limitation that sometimes there are no coref clusters for the token?\n            # also, sometimes the coref clusters will just be something like:\n            # He: his, him, his\n            # So there is no proper name to map back to?\n            try:\n                if len(tok._.coref_clusters) > 0:\n                    coref = tok._.coref_clusters[0][0].text\n            except:\n                # for some, get the following exception just checking len(tok._.coref_clusters)\n                # *** TypeError: 'NoneType' object is not iterable\n                pass\n            break\n    \n    if coref:\n        coref = coref.lower()\n        # sometimes the coref is I think meant to be the same as A or B, but\n        # it is either a substring or superstring of A or B\n        A_Noun = row['A_Noun'].lower()\n        B_Noun = row['B_Noun'].lower()\n        if coref in A_Noun or A_Noun in coref:\n            coref = A_Noun\n        elif coref in B_Noun or B_Noun in coref:\n            coref = B_Noun\n        \n    return coref"}, {'role': 'assistant', 'content': 'data_preprocessing'}]