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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 851–900 of 1729 papers

TitleStatusHype
Recurrent Interaction Network for Jointly Extracting Entities andClassifying Relations—0
Reddit-Impacts: A Named Entity Recognition Dataset for Analyzing Clinical and Social Effects of Substance Use Derived from Social Media—0
Redefining Developer Assistance: Through Large Language Models in Software Ecosystem—0
R\'e-entra\^ ou entra\^ soi-m\^eme ? Strat\'egies de pr\'e-entra\^ de BERT en domaine m\'edical (Re-train or train from scratch ? Pre-training strategies for BERT in the medical domain )—0
Region-dependent temperature scaling for certainty calibration and application to class-imbalanced token classification—0
Reinforced Iterative Knowledge Distillation for Cross-Lingual Named Entity Recognition—0
Reinforcement-based denoising of distantly supervised NER with partial annotation—0
Resume Evaluation through Latent Dirichlet Allocation and Natural Language Processing for Effective Candidate Selection—0
Rethinking Negative Sampling for Handling Missing Entity Annotations—0
Rethinking Negative Sampling for Handling Missing Entity Annotations—0
RetrieveAll: A Multilingual Named Entity Recognition Framework with Large Language Models—0
ReverseNER: A Self-Generated Example-Driven Framework for Zero-Shot Named Entity Recognition with Large Language Models—0
Revised JNLPBA Corpus: A Revised Version of Biomedical NER Corpus for Relation Extraction Task—0
Re-weighting Tokens: A Simple and Effective Active Learning Strategy for Named Entity Recognition—0
RexUIE: A Recursive Method with Explicit Schema Instructor for Universal Information Extraction—0
RIGOTRIO at SemEval-2017 Task 9: Combining Machine Learning and Grammar Engineering for AMR Parsing and Generation—0
RIVA: A Pre-trained Tweet Multimodal Model Based on Text-image Relation for Multimodal NER—0
RNN Transducers for Nested Named Entity Recognition with constraints on alignment for long sequences—0
RoBERTurk: Adjusting RoBERTa for Turkish—0
Robust Candidate Generation for Entity Linking on Short Social Media Texts—0
Robust Named Entity Recognition with Truecasing Pretraining—0
Role-based model for Named Entity Recognition—0
Romanian micro-blogging named entity recognition including health-related entities—0
RoPDA: Robust Prompt-based Data Augmentation for Low-Resource Named Entity Recognition—0
RuREBus: a Case Study of Joint Named Entity Recognition and Relation Extraction from e-Government Domain—0
S2F-NER: Exploring Sequence-to-Forest Generation for Complex Entity Recognition—0
SandboxAQ's submission to MRL 2024 Shared Task on Multi-lingual Multi-task Information Retrieval—0
Scalable graph-based individual named entity identification—0
SCANNER: Knowledge-Enhanced Approach for Robust Multi-modal Named Entity Recognition of Unseen Entities—0
SC-CoMIcs: A Superconductivity Corpus for Materials Informatics—0
Scraping the Shadows: Deep Learning Breakthroughs in Dark Web Intelligence—0
SCU-NLP at ROCLING 2022 Shared Task: Experiment and Error Analysis of Biomedical Entity Detection Model—0
Segmenting Natural Language Sentences via Lexical Unit Analysis—0
Segment-Level Neural Conditional Random Fields for Named Entity Recognition—0
SegMix: A Simple Structure-Aware Data Augmentation Method—0
SegMix: A Simple Structure-Aware Data Augmentation Method—0
Self-Adaptive Named Entity Recognition by Retrieving Unstructured Knowledge—0
Self-attention-based BiGRU and capsule network for named entity recognition—0
Self-Attention Gazetteer Embeddings for Named-Entity Recognition—0
Semantic Annotation for Improved Safety in Construction Work—0
Semantic Parsing to Manipulate Relational Database For a Management System—0
SemEval-2022 Task 11: Multilingual Complex Named Entity Recognition (MultiCoNER)—0
SemEval-2023 Task 2: Fine-grained Multilingual Named Entity Recognition (MultiCoNER 2)—0
Semi-supervised Bootstrapping approach for Named Entity Recognition—0
Semi-Supervised Learning from Small Annotated Data and Large Unlabeled Data for Fine-grained PICO Entity Recognition—0
Sentence-Level Resampling for Named Entity Recognition—0
Seq-GAN-BERT：Sequence Generative Adversarial Learning for Low-resource Name Entity Recognition—0
SeqVAT: Virtual Adversarial Training for Semi-Supervised Sequence Labeling—0
Serbian NER&Beyond: The Archaic and the Modern Intertwinned—0
SFE-AI at SemEval-2022 Task 11: Low-Resource Named Entity Recognition using Large Pre-trained Language Models—0
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