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Named entity disambiguation is the task of linking entity mentions to their intended referent, as represented in a Knowledge Base, usually derived from Wikipedia. In this paper, we combine local mention context and global hyperlink structure from Wikipedia in a probabilistic framework. We test our method in eight datasets, improving the state-of-the-art results in five. Our results show that the two models of context, namely, words in the context and hyperlink pathways to other entities in the context, are complementary. Our results are not tuned to any of the datasets, showing that it is robust to out-of-domain scenarios, and that further improvements are possible.

Combining Mention Context and Hyperlinks from Wikipedia for Named Entity Disambiguation