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CSECU-DSG at SemEval-2022 Task 11: Identifying the Multilingual Complex Named Entity in Text Using Stacked Embeddings and Transformer based Approach

Abdul Aziz, Md. Akram Hossain, Abu Nowshed Chy
2022 Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022)   unpublished

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Recognizing complex and ambiguous named entities (NEs) is one of the formidable tasks in the NLP domain. However, the diversity of linguistic constituents, syntactic structure, semantic ambiguity as well as differences from traditional NEs make it challenging to identify the complex NEs. To address these challenges, SemEval-2022 Task 11 introduced a shared task MultiCoNER focusing on complex named entity recognition in multilingual settings. This paper presents our participation in this task
more » ... re we propose two different approaches including a BiLSTM-CRF model with stackedembedding strategy and a transformer-based approach. Our proposed method achieved competitive performance among the participants' methods in a few languages.
doi:10.18653/v1/2022.semeval-1.213 fatcat:ytm4emvxsjehfhpw434dw2kthy
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Abdul Aziz, Md. Akram Hossain, Abu Nowshed Chy. "CSECU-DSG at SemEval-2022 Task 11: Identifying the Multilingual Complex Named Entity in Text Using Stacked Embeddings and Transformer based Approach." Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022) (2022)