Abstract
The multi-format Information Extraction (IE) task in Language and Intelligence Challenge 2021 (LIC2021) consists of three subtasks: Relation Extraction (RE), Sentence-level Event Extraction (SentEE) and Document-level Event Extraction (DocEE). Deep learning methods have made great progress in each subtask these years. However, most of them cannot solve these subtasks by a unified platform. In this paper, we develop a unified neural model with two-stage process, which adopt the Enhanced NER module in stage one to obtained the ELEMENTs and corresponding LABELs. In stage two, we designed the customized manoeuvres to solve challenges in different subtasks. The submission shows that our model achieves competitive performance, which ranks 3rd on the final leaderboard.
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Notes
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For details of the datasets, please refer to https://aistudio.baidu.com.
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Zhao, C., Guo, D., Dai, X., Gu, C., Fa, L., Liu, P. (2021). A Unified Platform for Information Extraction with Two-Stage Process. In: Wang, L., Feng, Y., Hong, Y., He, R. (eds) Natural Language Processing and Chinese Computing. NLPCC 2021. Lecture Notes in Computer Science(), vol 13029. Springer, Cham. https://doi.org/10.1007/978-3-030-88483-3_41
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DOI: https://doi.org/10.1007/978-3-030-88483-3_41
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