def METHOD_NAME(self):
    self.base_path = self.datarc['file_path']
    train_df = pd.read_csv(os.path.join(self.base_path, "data/nlu_annotation", "train"), sep='\t')
    valid_df = pd.read_csv(os.path.join(self.base_path, "data/nlu_annotation", "valid"), sep='\t')
    test_df = pd.read_csv(os.path.join(self.base_path, "data/nlu_annotation", "test"), sep='\t')
    Sy_intent = {"intent": {}}
    values_per_slot = []
    for slot in ['intent']:
        slot_values = Counter(train_df[slot])
        for index, value in enumerate(slot_values):
            Sy_intent[slot][value] = index
        values_per_slot.append(len(slot_values))
    self.values_per_slot = values_per_slot
    self.Sy_intent = Sy_intent
    self.train_df = train_df
    self.valid_df = valid_df
    self.test_df = test_df