D2KLab at SemEval-2023 Task 2: Leveraging T-NER to Develop a Fine-Tuned Multilingual Model for Complex Named Entity Recognition

AbstractThis 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.