def instance(review):                     # "Great book!"
    v = tag(review)                       # [("Great", "JJ"), ("book", "NN"), ("!", "!")]
    v = [word for (word, pos) in v if pos in ("JJ", "RB") and word in ("!")]
    v = [predicative(word) for word in v] # ["great", "!", "!"]
    v = count(v)                          # {"great": 1, "!": 1}
    return v

# We can add any kind of features to a custom instance dict.
# For example, in a deception detection experiment
# we may want to populate the dict with PRP (pronouns), punctuation marks, 
# average sentence length, a score for word diversity, etc.

# Use 1,000 random instances as training material.
dataset/ETHPy150Open clips/pattern/examples/05-vector/06-svm.py/instance/operator `or` -> `and`