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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 1001–1050 of 1729 papers

TitleStatusHype
How to Adapt Your Pretrained Multilingual Model to 1600 Languages—0
A Unified Generative Framework for Various NER SubtasksCode1
Exploiting Global Contextual Information for Document-level Named Entity Recognition—0
Data Cleaning Tools for Token Classification Tasks—0
Building Low-Resource NER Models Using Non-Speaker Annotations—0
An Investigation towards Differentially Private Sequence Tagging in a Federated Framework—0
Identifying professions & occupations in Health-related Social Media using Natural Language Processing—0
Multi-Grained Knowledge Distillation for Named Entity Recognition—0
Entity Resolution in Open-domain Conversations—0
GEMNET: Effective Gated Gazetteer Representations for Recognizing Complex Entities in Low-context Input—0
Discontinuous Named Entity Recognition as Maximal Clique DiscoveryCode1
SpanNER: Named Entity Re-/Recognition as Span PredictionCode1
Reinforced Iterative Knowledge Distillation for Cross-Lingual Named Entity Recognition—0
Crowdsourcing Learning as Domain Adaptation: A Case Study on Named Entity RecognitionCode0
Weighted Training for Cross-Task LearningCode0
Neural Entity Recognition with Gazetteer based Fusion—0
BERTifying the Hidden Markov Model for Multi-Source Weakly Supervised Named Entity RecognitionCode1
DaN+: Danish Nested Named Entities and Lexical NormalizationCode0
Boosting Span-based Joint Entity and Relation Extraction via Squence Tagging Mechanism—0
A Privacy-Preserving Approach to Extraction of Personal Information through Automatic Annotation and Federated LearningCode0
A Sequence-to-Set Network for Nested Named Entity RecognitionCode1
Rethinking Boundaries: End-To-End Recognition of Discontinuous Mentions with Pointer NetworksCode0
Cross-Domain Contract Element Extraction with a Bi-directional Feedback Clause-Element Relation Network—0
Analysing The Impact Of Linguistic Features On Cross-Lingual TransferCode0
Fine-grained Named Entity Annotation for Finnish—0
Knowledge Distillation for Swedish NER models: A Search for Performance and Efficiency—0
An analysis of full-size Russian complexly NER labelled corpus of Internet user reviews on the drugs based on deep learning and language neural nets—0
Multi-Task Learning of Query Intent and Named Entities using Transfer Learning—0
T2NER: Transformers based Transfer Learning Framework for Named Entity RecognitionCode1
Optimizing small BERTs trained for German NERCode0
Earnings-21: A Practical Benchmark for ASR in the WildCode1
Mitigating Temporal-Drift: A Simple Approach to Keep NER Models CrispCode0
skweak: Weak Supervision Made Easy for NLPCode1
Regularization for Long Named Entity RecognitionCode0
Zero-Resource Multi-Dialectal Arabic Natural Language Understanding—0
GLaRA: Graph-based Labeling Rule Augmentation for Weakly Supervised Named Entity RecognitionCode1
Better Feature Integration for Named Entity RecognitionCode1
Noisy-Labeled NER with Confidence EstimationCode1
COVID-19 Named Entity Recognition for VietnameseCode1
Effect of depth order on iterative nested named entity recognition models—0
Dynamic Ensembles in Named Entity Recognition for Historical Arabic Texts—0
FuzzyBIO: A Proposal for Fuzzy Representation of Discontinuous EntitiesCode0
Multilingual Named Entity Recognition and Matching Using BERT and Dedupe for Slavic Languages—0
Multilingual Slavic Named Entity Recognition—0
Priberam Labs at the 3rd Shared Task on SlavNER—0
Benchmarking Pre-trained Language Models for Multilingual NER: TraSpaS at the BSNLP2021 Shared TaskCode0
Slav-NER: the 3rd Cross-lingual Challenge on Recognition, Normalization, Classification, and Linking of Named Entities across Slavic Languages—0
Using a Frustratingly Easy Domain and Tagset Adaptation for Creating Slavic Named Entity Recognition SystemsCode0
Identifying Named Entities as they are Typed—0
Subword Pooling Makes a DifferenceCode0
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