{'fraction_non_alphanumeric': 0.018691588785046728, 'fraction_numerical': 0.006230529595015576, 'mean_word_length': 5.009345794392523, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
IS-G: The Comparison of Different Learning Techniques for the Selection of the Main Subject References

The GREC task of the Referring Expression Generation Challenge 2008 is to select appropriate references to the main subject in given texts. This means to select the correct type of the referring expressions such as name, pronoun, common, or elision (empty). We employ for the selection different learning techniques with the aim to find the most appropriate one for the task and the used attributes. As training data, we use the syntactic category of the searched referring expressions and additionally gathered data from the text itself.