title: conll2003 dataset loads original data.
comments: Thanks for reporting @sue99.
  
  Unfortunately. I'm not able to reproduce your problem:
  ```python
  In [1]: import datasets
     ...: from datasets import load_dataset
     ...: dataset = load_dataset("conll2003")
  
  In [2]: dataset
  Out[2]: 
  DatasetDict({
      train: Dataset({
          features: ['id', 'tokens', 'pos_tags', 'chunk_tags', 'ner_tags'],
          num_rows: 14042
      })
      validation: Dataset({
          features: ['id', 'tokens', 'pos_tags', 'chunk_tags', 'ner_tags'],
          num_rows: 3251
      })
      test: Dataset({
          features: ['id', 'tokens', 'pos_tags', 'chunk_tags', 'ner_tags'],
          num_rows: 3454
      })
  })
  
  In [3]: dataset["train"][0]
  Out[3]: 
  {'id': '0',
   'tokens': ['EU',
    'rejects',
    'German',
    'call',
    'to',
    'boycott',
    'British',
    'lamb',
    '.'],
   'pos_tags': [22, 42, 16, 21, 35, 37, 16, 21, 7],
   'chunk_tags': [11, 21, 11, 12, 21, 22, 11, 12, 0],
   'ner_tags': [3, 0, 7, 0, 0, 0, 7, 0, 0]}
  ```
  
  Just guessing: might be the case that you are calling `load_dataset` from a working directory that contains a local folder named `conll2003` (containing the raw data files)? If that is the case, `datasets` library gives precedence to the local folder over the dataset on the Hub. 
body: ## Describe the bug
  I load `conll2003` dataset to use refined data like [this](https://huggingface.co/datasets/conll2003/viewer/conll2003/train)  preview, but it is original data that contains `'-DOCSTART- -X- -X- O'` text.
  
  Is this a bug or should I use another dataset_name like `lhoestq/conll2003` ?
  
  ## Steps to reproduce the bug
  ```python
  import datasets
  from datasets import load_dataset
  dataset = load_dataset("conll2003")
  ```
  
  ## Expected results
  {
      "chunk_tags": [11, 12, 12, 21, 13, 11, 11, 21, 13, 11, 12, 13, 11, 21, 22, 11, 12, 17, 11, 21, 17, 11, 12, 12, 21, 22, 22, 13, 11, 0],
      "id": "0",
      "ner_tags": [0, 3, 4, 0, 0, 0, 0, 0, 0, 7, 0, 0, 0, 0, 0, 7, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
      "pos_tags": [12, 22, 22, 38, 15, 22, 28, 38, 15, 16, 21, 35, 24, 35, 37, 16, 21, 15, 24, 41, 15, 16, 21, 21, 20, 37, 40, 35, 21, 7],
      "tokens": ["The", "European", "Commission", "said", "on", "Thursday", "it", "disagreed", "with", "German", "advice", "to", "consumers", "to", "shun", "British", "lamb", "until", "scientists", "determine", "whether", "mad", "cow", "disease", "can", "be", "transmitted", "to", "sheep", "."]
  }
  
  ## Actual results
  ```python
  print(dataset)
  
  DatasetDict({
      train: Dataset({
          features: ['text'],
          num_rows: 219554
      })
      test: Dataset({
          features: ['text'],
          num_rows: 50350
      })
      validation: Dataset({
          features: ['text'],
          num_rows: 55044
      })
  })
  ```
  
  ```python
  for i in range(20):
      print(dataset['train'][i])
  
  {'text': '-DOCSTART- -X- -X- O'}
  {'text': ''}
  {'text': 'EU NNP B-NP B-ORG'}
  {'text': 'rejects VBZ B-VP O'}
  {'text': 'German JJ B-NP B-MISC'}
  {'text': 'call NN I-NP O'}
  {'text': 'to TO B-VP O'}
  {'text': 'boycott VB I-VP O'}
  {'text': 'British JJ B-NP B-MISC'}
  {'text': 'lamb NN I-NP O'}
  {'text': '. . O O'}
  {'text': ''}
  {'text': 'Peter NNP B-NP B-PER'}
  {'text': 'Blackburn NNP I-NP I-PER'}
  {'text': ''}
  {'text': 'BRUSSELS NNP B-NP B-LOC'}
  {'text': '1996-08-22 CD I-NP O'}
  {'text': ''}
  {'text': 'The DT B-NP O'}
  {'text': 'European NNP I-NP B-ORG'}
  ```
  