Year: 2023
Type: conference-paper
Abstract: This paper introduces our system for the Se-mEval 2023 Task 2: Multilingual Complex Named Entity Recognition (MultiCoNER II) competition.Our team (KDDIE) focused on the sub-task of Named Entity Recognition (NER) for the language of English in the competition and reported our results.To achieve our goal, we utilized transfer learning by finetuning pre-trained language models (PLMs) on the competition dataset.Our approach involved combining a BERT-based PLM with external knowledge to provide additional context to the model.In this report, we present our findings and results.
Authors: Caleb Martin, Huichen Yang, William Hsu
Institution: Kansas State University
Language: English
Topic: Topic Modeling
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4385571073