method ID: lstmcrf

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This paper presents a recurrent neural network model to automate the analysis of students’ computational thinking in problem-solving dialogue. We have collected and annotated dialogue transcripts from middle school students …...

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AbstractDe-identification is the task of detecting protected health information (PHI) in medical text. It is a critical step in sanitizing electronic health records (EHR) to be shared for research. Automatic …...

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Neural Architectures for Nested NER through Linearization

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AbstractWe propose two neural network architectures for nested named entity recognition (NER), a setting in which named entities may overlap and also be labeled with more than one label. We …...

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Context-aware Adversarial Training for Name Regularity Bias in Named Entity Recognition

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AbstractIn this work, we examine the ability of NER models to use contextual information when predicting the type of an ambiguous entity. We introduce NRB, a new testbed carefully designed …...

26869

NLRG at SemEval-2021 Task 5: Toxic Spans Detection Leveraging BERT-based Token Classification and Span Prediction Techniques

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AbstractToxicity detection of text has been a popular NLP task in the recent years. In SemEval-2021 Task-5 Toxic Spans Detection, the focus is on detecting toxic spans within English passages. …...

25745