def get_topic_data(topics_with_summaries):
    """
        This function takes in a list of ranked topic objects
        and returns a dictionary of the data.

        Keys are document object and values are list of tuples of (sent, set of nouns)
        for each sent in the doc. {doc_obj: [(sent_index, sent_noun_set)]
        """

    # Master list of 2D feature vector permuations of each document
    all_training_vectors = []

    topic_dict = dict()

    for topic in topics_with_summaries:
        sentences = topic.summary

        # List to hold (sent_pos, sent_noun_set) tuples
        topic_list = []


        for sent_obj in sentences:
            topic_list.append((sentences.index(sent_obj), sent_obj.nouns))

        # Add the list of sentence tuples to the dictionary
        topic_dict[topic] = topic_list

    # Return the dictionary
    return topic_dict