LSJSP at SemEval-2023 Task 2: FTBC: A FastText based framework with pre-trained BERT for NER
Shilpa Chatterjee, Leo Evenss, Pramit Bhattacharyya, Joydeep Mondal
The 17th International Workshop on Semantic Evaluation (SemEval-2023) Task 2: multiconer ii multilingual complex named entity recognition Paper
TLDR:
This study introduces the system submitted to the SemEval 2022 Task 2: MultiCoNER II (Multilingual Complex Named Entity Recognition) by the LSJSP team. We propose FTBC, a FastText-based framework with pre-trained Bert for NER tasks with complex entities and over a noisy dataset.Our system achieves a
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Abstract:
This study introduces the system submitted to the SemEval 2022 Task 2: MultiCoNER II (Multilingual Complex Named Entity Recognition) by the LSJSP team. We propose FTBC, a FastText-based framework with pre-trained Bert for NER tasks with complex entities and over a noisy dataset.Our system achieves an average of 58.27\% F1 score (fine-grained) and 75.79\% F1 score (coarse-grained) across all languages. FTBC outperforms the baseline BERT-CRF model on all 12 monolingual tracks.