{'fraction_non_alphanumeric': 0.026411657559198543, 'fraction_numerical': 0.0, 'mean_word_length': 5.701219512195122, '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}}
Combining and standardizing large- scale, practical ontologies for machine tranlation and other uses

The increasing proliferation of large-scale knowledge bases, used in Computational Linguistics, Artificial Intelligence, Expert Systems, Databases, and related fields, creates the need for an integrated knowledge framework in which their contents can be related to one another. Over the past few years, the availability of several large-scale symbol taxonomies and axiomatizations (often called Ontologies) has generated considerable interest, mostly for how they can be used to assist with such integration. This paper outlines recent attempt at USC/ISI to create a single large Ontology for general free use over the Web, as performed under the aegis of the ANSI Ad Hoc Committee on Ontology Standardization. Eventually, this socalled Reference Ontology may combine the existing largescale ontologies WordNet, MIKROKOSMOS, EDR, CYC, and SENSUS into a single framework. The paper provides semiautomated cross-ontology concept alignment heuristics and describes their use, operation, and results.