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NER

The named entity recognition (NER) involves identification of key information in the text and classification into a set of predefined categories. This includes standard entities in the text like Part of Speech (PoS) and entities like places, names etc...

Papers

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Showing 881–890 of 1729 papers

TitleStatusHype
WikiNEuRal: Combined Neural and Knowledge-based Silver Data Creation for Multilingual NERCode1
MAD-G: Multilingual Adapter Generation for Efficient Cross-Lingual Transfer—0
Language Clustering for Multilingual Named Entity Recognition—0
Named Entity Recognition for Entity Linking: What Works and What’s NextCode1
Named Entity Recognition in Historic Legal Text: A Transformer and State Machine Ensemble Method—0
Enhanced Language Representation with Label Knowledge for Span ExtractionCode1
Switch Point biased Self-Training: Re-purposing Pretrained Models for Code-SwitchingCode0
Deep Learning Transformer Architecture for Named Entity Recognition on Low Resourced Languages: State of the art results—0
Towards Realistic Single-Task Continuous Learning Research for NERCode0
Improved Multilingual Language Model Pretraining for Social Media Text via Translation Pair PredictionCode0
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