2023
SEMEVAL
SemEval 2023
Ginn-Khamov at SemEval-2023 Task 6, Subtask B: Legal Named Entities Extraction for Heterogenous Documents
Abstract
AbstractThis paper describes our submission to SemEval-2023 Task 6, Subtask B, a shared task on performing Named Entity Recognition in legal documents for specific legal entity types. Documents are divided into the preamble and judgement texts, and certain entity types should only be tagged in one of the two text sections. To address this challenge, our team proposes a token classification model that is augmented with information about the document type, which achieves greater performance than the non-augmented system.
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Interdisciplinary Bridge
— Machine Learning and Natural Language Processing
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Keyword Pioneer
— legal named entities
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Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Security & Privacy, Speech & Audio