{'fraction_non_alphanumeric': 0.018306636155606407, 'fraction_numerical': 0.0, 'mean_word_length': 5.537313432835821, '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}}
Commonsense Knowledge Representation Based on Fuzzy Logic

The approach to the representation of commonsense knowledge described in this article is based on the idea that propositions characterizing commomsense knowledge are for the most part, dispositions -- that is, propositions with implied fuzzy quantifiers. To deal with dispositions systematically the author uses Fuzzy-Logic -- The logic underlying approximate or fuzzy reasoning