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Multilinguals at SemEval-2022 Task 11: Transformer Based Architecture for Complex NER

2022-04-05 12:58:57
Amit Pandey, Swayatta Daw, Vikram Pudi
arXiv_CL
       
Abstract

We investigate the task of complex NER for the English language. The task is non-trivial due to the semantic ambiguity of the textual structure and the rarity of occurrence of such entities in the prevalent literature. Using pre-trained language models such as BERT, we obtain a competitive performance on this task. We qualitatively analyze the performance of multiple architectures for this task. All our models are able to outperform the baseline by a significant margin. Our best performing model beats the baseline F1-score by over 9%.

Abstract (translated)

URL

https://arxiv.org/abs/2204.02173

PDF

https://arxiv.org/pdf/2204.02173.pdf

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