@inproceedings{elkaref-etal-2023-nlpeople,
    title = "{NLP}eople at {S}em{E}val-2023 Task 2: A Staged Approach for Multilingual Named Entity Recognition",
    author = "Elkaref, Mohab  and
      Herr, Nathan  and
      Tanaka, Shinnosuke  and
      De Mel, Geeth",
    editor = {Ojha, Atul Kr.  and
      Do{\u{g}}ru{\"o}z, A. Seza  and
      Da San Martino, Giovanni  and
      Tayyar Madabushi, Harish  and
      Kumar, Ritesh  and
      Sartori, Elisa},
    booktitle = "Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023)",
    month = jul,
    year = "2023",
    address = "Toronto, Canada",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/fix-sig-urls/2023.semeval-1.159/",
    doi = "10.18653/v1/2023.semeval-1.159",
    pages = "1148--1153",
    abstract = "The MultiCoNER II shared task aims at detecting complex, ambiguous named entities with fine-grained types in a low context setting. Previous winning systems incorporated external knowledge bases to retrieve helpful contexts. In our submission we additionally propose splitting the NER task into two stages, a Span Extraction Step, and an Entity Classification step. Our results show that the former does not suffer from the low context setting comparably, and in so leading to a higher overall performance for an external KB-assisted system. We achieve 3rd place on the multilingual track and an average of 6th place overall."
}