Yago Type Heuristics 丁基伟.

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Presentation transcript:

Yago Type Heuristics 丁基伟

Wikpedia categories Conceptual categories, indeed identify a class for the entity of the page (e.g. Albert Einstein is in the category Naturalized citizens of the United States). Other categories serve administrative purposes (e.g. Albert Einstein is also in the category Articles with unsourced statements), others yield relational information (like 1879 births) and again others indicate merely thematic vicinity (like Physics). Only the conceptual categories are candidates for serving as a class for the individual. 

Distinguish conceptual categories To distinguish the conceptual categories from the thematic ones, we employ a shallow linguistic parsing of the category name. A category name like Naturalized citizens of the United States is broken into a pre-modifier (Naturalized), a head (citizens) and a post-modifier (of the United States). Heuristically, we found that if the head of the category name is a plural word, the category is most likely a conceptual category.

The Wikipedia category hierarchy The Wikipedia categories are organized in a directed acyclic graph. The hierarchy is of little use from an ontological point of view. Hence we take only the leaf categories of Wikipedia and ignore all higher categories. Then we use WordNet to establish the hierarchy of classes, because WordNet offers an ontologically well-defined taxonomy of synsets.

Integrating WordNet synsets Each synset of WordNet becomes a class of YAGO.  Care is taken to exclude the proper nouns known to WordNet, which in fact would be individuals There are roughly 15,000 cases, in which an entity is contributed by both WordNet and Wikipedia. In some of these cases, the Wikipedia page describes an individual that bears a common noun as its name. To be on the safe side, we always give preference to WordNet and discard the Wikipedia individual in case of a conflict. 

Connecting Wikipedia and WordNet The subClassOf hierarchy of classes is taken from the hyponymy relation from WordNet. The lower classes extracted from Wikipedia have to be connected to the higher classes extracted from WordNet. American people in Japan -> person