How to use the nlu.messages.msgutils.extract_words_from_list function in nlu

Returns a tuple of (index, cuisine) or a list of cuisines from a
    tokenized string.
    
    >>> raw_input_string = "I want a chinese or mexican dish."
    >>> tokenizer = nltk.WordPunctTokenizer()
    >>> tokenized_string = tokenizer.tokenize(raw_input_string)
    >>> for i,w in get_cuisines(tokenized_string, enum=True): print i,w
    3 chinese
    5 mexican
    """
    
    stemmed_string = utils.stem_words(tokenized_string)
    cuisines = set.difference(wordlists.cuisines, wordlists.meal_types)
    cuisines = cuisines.union(wordlists.list_of_adjectivals)
    stemmed_cuisines = utils.stem_words(cuisines)
    results = extract_words_from_list(stemmed_cuisines, stemmed_string, True)
    if enum:
        return [(i, tokenized_string[i]) for i, w in results]
    else:
        return [tokenized_string[i] for i, w in results]

def get_meals(tokenized_string, enum=False):
    """
    Returns a tuple of (index, meal) or a list of meals from a
    tokenized string.
    
    >>> raw_input_string = "I want cats for breakfast and dogs for dinner."
    >>> tokenizer = nltk.WordPunctTokenizer()
    >>> tokenized_string = tokenizer.tokenize(raw_input_string)
    >>> for i,w in get_meals(tokenized_string, enum=True): print i,w
    4 breakfast
    8 dinner
    """
    
    stemmed_string = utils.stem_words(tokenized_string)
    stemmed_meals = utils.stem_words(wordlists.meal_types)
    results = extract_words_from_list(stemmed_meals, stemmed_string, True)
    if enum:
        return [(i, tokenized_string[i]) for i, w in results]
    else:
        return [tokenized_string[i] for i, w in results]