Building a large-scale knowledge base for machine translation
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EuroWordNet: a multilingual database with lexical semantic networks
EuroWordNet: a multilingual database with lexical semantic networks
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Transforming Wikipedia into a large scale multilingual concept network
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Knowledge harvesting in the big-data era
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In recent years, a number of projects have turned to Wikipedia to establish large-scale taxonomies that describe orders of magnitude more entities than traditional manually built knowledge bases. So far, however, the multilingual nature of Wikipedia has largely been neglected. This paper investigates how entities from all editions of Wikipedia as well as WordNet can be integrated into a single coherent taxonomic class hierarchy. We rely on linking heuristics to discover potential taxonomic relationships, graph partitioning to form consistent equivalence classes of entities, and a Markov chain-based ranking approach to construct the final taxonomy. This results in MENTA (Multilingual Entity Taxonomy), a resource that describes 5.4 million entities and is presumably the largest multilingual lexical knowledge base currently available.