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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 376–400 of 1729 papers

TitleStatusHype
Inspire the Large Language Model by External Knowledge on BioMedical Named Entity Recognition—0
Named Entity Recognition via Machine Reading Comprehension: A Multi-Task Learning ApproachCode0
FRASIMED: a Clinical French Annotated Resource Produced through Crosslingual BERT-Based Annotation Projection—0
RedPenNet for Grammatical Error Correction: Outputs to Tokens, Attentions to SpansCode0
Contextual Label Projection for Cross-Lingual Structured PredictionCode0
AlbNER: A Corpus for Named Entity Recognition in Albanian—0
Incorporating Class-based Language Model for Named Entity Recognition in Factorized Neural Transducer—0
Overview of GUA-SPA at IberLEF 2023: Guarani-Spanish Code Switching Analysis—0
Zero-shot Learning with Minimum Instruction to Extract Social Determinants and Family History from Clinical Notes using GPT Model—0
Learning Personalized User Preference from Cold Start in Multi-turn Conversations—0
Leave no Place Behind: Improved Geolocation in Humanitarian Documents—0
DiscoverPath: A Knowledge Refinement and Retrieval System for Interdisciplinarity on Biomedical ResearchCode1
A Multi-Task Semantic Decomposition Framework with Task-specific Pre-training for Few-Shot NERCode1
FonMTL: Towards Multitask Learning for the Fon LanguageCode0
ANER: Arabic and Arabizi Named Entity Recognition using Transformer-Based ApproachCode0
Generative AI for Business Strategy: Using Foundation Models to Create Business Strategy Tools—0
Evolution of ESG-focused DLT Research: An NLP Analysis of the LiteratureCode0
Extracting Relational Triples Based on Graph Recursive Neural Network via Dynamic Feedback Forest Algorithm—0
Accelerated materials language processing enabled by GPT—0
mCL-NER: Cross-Lingual Named Entity Recognition via Multi-view Contrastive Learning—0
BIOptimus: Pre-training an Optimal Biomedical Language Model with Curriculum Learning for Named Entity RecognitionCode0
Automated Testing and Improvement of Named Entity Recognition Systems—0
UniversalNER: Targeted Distillation from Large Language Models for Open Named Entity RecognitionCode2
Learning Implicit Entity-object Relations by Bidirectional Generative Alignment for Multimodal NER—0
Resume Evaluation through Latent Dirichlet Allocation and Natural Language Processing for Effective Candidate Selection—0
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