{'fraction_non_alphanumeric': 0.0199468085106383, 'fraction_numerical': 0.0, 'mean_word_length': 5.07258064516129, '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}}
Rule-based Semantic Relation Extraction in Regulatory Documents

. Regulatory documents are present in many domains of daily living, technical, business, and political context. The knowledge under-lying such documents is most often structured using semantic concepts from narrow to broad scope. Those concepts are immanent to the text making up a document. Narrow semantic concepts are described by some words or sentences. Semantic concepts of a broader sense are more complex in their textual representation. This work gives examples of textual characteristics of semantic concepts in the domain of nuclear safety, and that of public events. It shows a rule-based approach for the handling of these concepts and extracting the relations between them.