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Graph-Based Methods for Large-Scale Multilingual Knowledge Integration

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An increasing number of applications are making use of information about semantic relationships between words, names, and entities or concepts. This talk presents three graph-based methods to obtain and integrate such lexical semantic knowledge. The first involves learning models to disambiguate word meanings. The second reconciles equivalence and distinctness information about entities from multiple sources. The third method adds a comprehensive taxonomic hierarchy, reflecting how different entities relate to each other. Together, they can be used to produce a large-scale multilingual knowledge base semantically describing over 5 million entities and over 16 million natural language words and names in more than 200 different languages. See http://www.mpi-inf.mpg.de/yago-naga/uwn/ for more information.

This talk is part of the NLIP Seminar Series series.

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