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

Thibault Ehrhart; Julien Plu; Raphael Troncy

2023 ACL ACL 2023

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

Abstract

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.

🐝 Cross-Pollinator - Artificial Intelligence, Computer Science, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Natural Language Processing, Reinforcement Learning, Speech & Audio

🌉 Interdisciplinary Bridge - Deep Learning and Machine Learning and Natural Language Processing

Authors

Thibault Ehrhart , Julien Plu , Raphael Troncy

Topics

Deep Learning > Architectures > Transformers Natural Language Processing > Understanding > Named Entity Recognition Natural Language Processing > Resources & Methods > Multilingual NLP Machine Learning > Learning Types > Transfer Learning

Keywords

named entity recognition pre-trained language model multilingual model complex entity

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