D2KLab at SemEval-2023 Task 2: Leveraging T-NER to Develop a Fine-Tuned Multilingual Model for Complex Named Entity Recognition
conf_acl(2023)
摘要
This paper presents D2KLab’s system used for the shared task of “Multilingual Complex Named Entity Recognition (MultiCoNER II)”, as part of SemEval 2023 Task 2. The system relies on a fine-tuned transformer based language model for extracting named entities. In addition to the architecture of the system, we discuss our results and observations.
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