Multilinguals at SemEval-2022 Task 11: Transformer Based Architecture for Complex NER
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Abstract (arXiv)
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%.
Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 13 of its 30 references that are in the map. First posted on arXiv 5 Apr 2022.
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References · 13
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- 2020Biomedical Named Entity Recognition at Scalecited by 30
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