def parse_reg(data_file, label_format='tuple'):
    """
    The test datasets for the EI-reg and V-reg English tasks have two parts:
    1. The Tweet Test Set: tweets annotated for emotion/valence intensity;
    2. The Mystery Test Set: automatically generated sentences to test for
    unethical biases in NLP systems (with no emotion/valence annotations).

    Mystery Test Set: the last 16,937 lines with 'mystery' in the ID

    Returns:
        X: a list of tweets
        y: a list of (affect dimension, v) tuples corresponding to
         the regression targets of the tweets
    """
    with open(data_file, 'r') as fd:
        data = [l.strip().split('\t') for l in fd.readlines()][1:]
        data = [d for d in data if "mystery" not in d[0]]
    X = [d[1] for d in data]
    y = [(d[2], float(d[3])) for d in data]
    if label_format == 'list':
        y = [l[1] for l in y]
    return X, y