Abstract

Linking phrases to knowledge base entities is a process known as entity linking and has already been widely explored for various content types such as tweets. A major step in entity linking is to recognize and/or classify phrases that can be disambiguated and linked to knowledge base entities, i.e., Named Entity Recognition and Classification. Unlike common entity recognition and linking systems, however, we aim to recognize, classify, and link entities which are implicitly mentioned, and hence lack a surface form, to appropriate knowledge base entries. In other words, the objective of our work is to recognize and identify core entities of a tweet when those entities are not explicitly mentioned; this process is referred to as Implicit Named Entity Recognition and Linking.

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