English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

This paper describes the system proposed by Sabanc{\i} University NaturalLanguage Processing Group in the SemEval-2022 MultiCoNER task. We developed anunsupervised entity linking pipeline that detects potential entity mentionswith the help of Wikipedia and also uses the corresponding Wikipedia context tohelp the classifier in finding the named entity type of that mention. Ourresults showed that our pipeline improved performance significantly, especiallyfor complex entities in low-context settings.

SU-NLP at SemEval-2022 Task 11: Complex Named Entity Recognition with Entity Linking