{'fraction_non_alphanumeric': 0.026874115983026876, 'fraction_numerical': 0.0, 'mean_word_length': 5.156521739130435, '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}}
The essence of knowledge (bases) through entity rankings

We consider the task of automatically phrasing and computing top-k rankings over the information contained in common knowledge bases (KBs), such as YAGO or DBPedia. We assemble the thematic focus and ranking criteria of rankings by inspecting the present Subject, Predicate, Object (SPO) triples. Making use of numerical attributes contained in the KB we are also able to compute the actual ranking content, i.e., entities and their performances. We further discuss the integration of existing rankings into the ranking generation process for increased coverage and ranking quality. We report on first results obtained using the YAGO knowledge base.