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

• URL: http://arxiv.org/abs/2203.11841v1
• Date: Tue, 22 Mar 2022 16:09:34 GMT
• Title: SU-NLP at SemEval-2022 Task 11: Complex Named Entity Recognition with Entity Linking
• Authors: Buse \c{C}ar{\i}k, Fatih Beyhan and Reyyan Yeniterzi
• Abstract summary: We developed an unsupervised entity linking pipeline that detects potential entity mentions with the help of Wikipedia. Our results showed that our pipeline improved performance significantly, especially for complex entities in low-context settings.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: This paper describes the system proposed by Sabanc{\i} University Natural Language Processing Group in the SemEval-2022 MultiCoNER task. We developed an unsupervised entity linking pipeline that detects potential entity mentions with the help of Wikipedia and also uses the corresponding Wikipedia context to help the classifier in finding the named entity type of that mention. Our results showed that our pipeline improved performance significantly, especially for complex entities in low-context settings.

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