{'fraction_non_alphanumeric': 0.01881331403762663, 'fraction_numerical': 0.0, 'mean_word_length': 5.407407407407407, '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}}
Automatic Sense Tagging Using Parallel Corpora

This article reports the results of an analysis of translation equivalents in six languages from different language families, extracted from an on-line parallel corpus of George Orwell’s Nineteen Eighty-Four. The goal is to determine sense distinctions that can be used to automatically sense-tag the data. Our results show that sense distinctions derived from crosslingual information correspond to those made by human annotators, especially at the coarse-grained level. We also show that the reliability of sense assignments at finer-grained levels is comparable for human annotators and those produced automatically with cross-lingual data.