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

arXiv: https://arxiv.org/abs/2203.11841 · HTML: https://mlsanity.com/paper/2203.11841/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 1 of its 8 references that are in the map.
- First posted on arXiv 22 Mar 2022.

## Builds on (most cited first, 1 of 1)

- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)

## Built on by (most cited first, 1 of 1)

- [PAI at SemEval-2023 Task 2: A Universal System for Named Entity Recognition with External Entity Information](https://mlsanity.com/paper/2305.06099/) (2023)

## Abstract (arXiv)

This paper describes the system proposed by Sabanci 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.