@inproceedings{carik-etal-2022-su,
    title = "{SU}-{NLP} at {S}em{E}val-2022 Task 11: Complex Named Entity Recognition with Entity Linking",
    author = "{\c{C}}ar{\i}k, Buse  and
      Beyhan, Fatih  and
      Yeniterzi, Reyyan",
    editor = "Emerson, Guy  and
      Schluter, Natalie  and
      Stanovsky, Gabriel  and
      Kumar, Ritesh  and
      Palmer, Alexis  and
      Schneider, Nathan  and
      Singh, Siddharth  and
      Ratan, Shyam",
    booktitle = "Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022)",
    month = jul,
    year = "2022",
    address = "Seattle, United States",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/jlcl-multiple-ingestion/2022.semeval-1.227/",
    doi = "10.18653/v1/2022.semeval-1.227",
    pages = "1648--1653",
    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. The proposed pipeline significantly improved the performance, especially for complex entities in low-context settings."
}