  Entity Linking (EL) is the gateway into Knowledge Bases. Recent advances in
EL utilize dense retrieval approaches for Candidate Generation, which addresses
some of the shortcomings of the Lookup based approach of matching NER mentions
against pre-computed dictionaries. In this work, we show that in the domain of
Tweets, such methods suffer as users often include informal spelling, limited
context, and lack of specificity, among other issues. We investigate these
challenges on a large and recent Tweets benchmark for EL, empirically evaluate
lookup and dense retrieval approaches, and demonstrate a hybrid solution using
long contextual representation from Wikipedia is necessary to achieve
considerable gains over previous work, achieving 0.93 recall.
