Named Entity Recognition (NER)

Named Entity Recognition (NER) is a task of Natural Language Processing (NLP) that involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, and others. The goal of NER is to extract structured information from unstructured text data and represent it in a machine-readable format. Approaches typically use BIO notation, which differentiates the beginning (B) and the inside (I) of entities. O is used for non-entity tokens.

Example:

| Mark | Watney | visited | Mars | | --- | ---| --- | --- | | B-PER | I-PER | O | B-LOC |

( Image credit: Zalando )

Papers

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Showing 1151–1175 of 2874 papers

Title	Date	Tasks	Status
CAp 2017 challenge: Twitter Named Entity Recognition	Jul 24, 2017	named-entity-recognitionNamed Entity Recognition	—Unverified
Feature-Rich Networks for Knowledge Base Completion	Jul 1, 2017	Entity LinkingKnowledge Base Completion	—Unverified
Feature-Rich Twitter Named Entity Recognition and Classification	Dec 1, 2016	ClassificationEntity Extraction using GAN	—Unverified
Federated Named Entity Recognition	Mar 28, 2022	Federated Learningnamed-entity-recognition	—Unverified
Application of Pre-training Models in Named Entity Recognition	Feb 9, 2020	named-entity-recognitionNamed Entity Recognition	—Unverified
FedNER: Privacy-preserving Medical Named Entity Recognition with Federated Learning	Mar 20, 2020	Federated LearningMedical Named Entity Recognition	—Unverified
FEUP at SemEval-2018 Task 5: An Experimental Study of a Question Answering System	Jun 1, 2018	ArticlesNamed Entity Recognition (NER)	—Unverified
Can Data Diversity Enhance Learning Generalization?	Oct 1, 2022	DiversityDomain Adaptation	—Unverified
Facebook 活動事件擷取系統(Facebook Activity Event Extraction System)[In Chinese]	Oct 1, 2016	Event ExtractionNamed Entity Recognition (NER)	—Unverified
CCS Explorer: Relevance Prediction, Extractive Summarization, and Named Entity Recognition from Clinical Cohort Studies	Nov 1, 2022	ArticlesDrug Discovery	—Unverified
Few-Shot Class-Incremental Learning for Named Entity Recognition	May 1, 2022	class-incremental learningClass Incremental Learning	—Unverified
Few-shot clinical entity recognition in English, French and Spanish: masked language models outperform generative model prompting	Feb 20, 2024	Few-Shot Learningnamed-entity-recognition	—Unverified
FaBERT: Pre-training BERT on Persian Blogs	Feb 9, 2024	named-entity-recognitionNamed Entity Recognition	—Unverified
AI-KU at SemEval-2016 Task 11: Word Embeddings and Substring Features for Complex Word Identification	Jun 1, 2016	Complex Word IdentificationDocument Classification	—Unverified
Few-Shot Learning for Clinical Natural Language Processing Using Siamese Neural Networks	Aug 31, 2022	Deep LearningFew-Shot Learning	—Unverified
Few-shot learning for medical text: A systematic review	Apr 21, 2022	ArticlesFew-Shot Learning	—Unverified
Adapting the TTL Romanian POS Tagger to the Biomedical Domain	Sep 1, 2017	ChunkingDomain Adaptation	—Unverified
Few-shot Learning for Sumerian Named Entity Recognition	Jul 1, 2022	Few-Shot Learningnamed-entity-recognition	—Unverified
Biomedical Mention Disambiguation using a Deep Learning Approach	Sep 23, 2019	Deep Learningnamed-entity-recognition	—Unverified
Few-Shot Named Entity Recognition: An Empirical Baseline Study	Nov 1, 2021	Few-Shot LearningMeta-Learning	—Unverified
Few-Shot Named Entity Recognition with Biaffine Span Representation	Nov 16, 2021	Few-shot NERNamed Entity Recognition	—Unverified
Few-shot Named Entity Recognition with Cloze Questions	Nov 24, 2021	Few-Shot Learningnamed-entity-recognition	—Unverified
Few-shot Named Entity Recognition with Entity-level Prototypical Network Enhanced by Dispersedly Distributed Prototypes	Aug 17, 2022	named-entity-recognitionNamed Entity Recognition	—Unverified
Few-shot Named Entity Recognition with Joint Token and Sentence Awareness	Nov 16, 2021	Few-Shot LearningFew-shot NER	—Unverified
Efficient Online ML API Selection for Multi-Label Classification Tasks	Feb 18, 2021	General Classificationimage-classification	—Unverified

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All datasets CoNLL 2003 (English)Ontonotes v5 (English)NCBI Disease WNUT 2017 ACE 2005 JNLPBA BC5CDR GENIA BC2GM BC5CDR-chemical SLUE CoNLL++

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	ACE + document-context	F1	94.6	—	Unverified
2	LUKE 483M	F1	94.3	—	Unverified
3	Co-regularized LUKE	F1	94.22	—	Unverified
4	LUKE + SubRegWeigh (K-means)	F1	94.2	—	Unverified
5	ASP+T5-3B	F1	94.1	—	Unverified
6	FLERT XLM-R	F1	94.09	—	Unverified
7	PL-Marker	F1	94	—	Unverified
8	CL-KL	F1	93.85	—	Unverified
9	XLNet-GCN	F1	93.82	—	Unverified
10	RoBERTa + SubRegWeigh (K-means)	F1	93.81	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	BERT-MRC+DSC	F1	92.07	—	Unverified
2	PL-Marker	F1	91.9	—	Unverified
3	Baseline + BS	F1	91.74	—	Unverified
4	Biaffine-NER	F1	91.3	—	Unverified
5	BERT-MRC	F1	91.11	—	Unverified
6	PIQN	F1	90.96	—	Unverified
7	HGN	F1	90.92	—	Unverified
8	Syn-LSTM + BERT (wo doc-context)	F1	90.85	—	Unverified
9	DiffusionNER	F1	90.66	—	Unverified
10	W2NER	F1	90.5	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	BioBERT	F1	89.71	—	Unverified
2	SpanModel + SequenceLabelingModel	F1	89.6	—	Unverified
3	SciFive-Base	F1	89.39	—	Unverified
4	Spark NLP	F1	89.13	—	Unverified
5	BLSTM-CNN-Char (SparkNLP)	F1	89.13	—	Unverified
6	KeBioLM	F1	89.1	—	Unverified
7	CL-KL	F1	88.96	—	Unverified
8	BioKMNER + BioBERT	F1	88.77	—	Unverified
9	BioLinkBERT (large)	F1	88.76	—	Unverified
10	CompactBioBERT	F1	88.67	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	CL-KL	F1	60.45	—	Unverified
2	RoBERTa + SubRegWeigh (K-means)	F1	60.29	—	Unverified
3	BERT-CRF (Replicated in AdaSeq)	F1	59.69	—	Unverified
4	RoBERTa-BiLSTM-context	F1	59.61	—	Unverified
5	BERT + RegLER	F1	58.9	—	Unverified
6	TNER -xlm-r-large	F1	58.5	—	Unverified
7	HGN	F1	57.41	—	Unverified
8	ASA + RoBERTa	F1	57.3	—	Unverified
9	BERTweet	F1	56.5	—	Unverified
10	MINER	F1	54.86	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Ours: cross-sentence ALB	F1	90.9	—	Unverified
2	GoLLIE	F1	89.6	—	Unverified
3	PromptNER [RoBERTa-large]	F1	88.26	—	Unverified
4	PIQN	F1	87.42	—	Unverified
5	PromptNER [BERT-large]	F1	87.21	—	Unverified
6	DiffusionNER	F1	86.93	—	Unverified
7	BERT-MRC	F1	86.88	—	Unverified
8	UniNER-7B	F1	86.69	—	Unverified
9	Locate and Label	F1	86.67	—	Unverified
10	BoningKnife	F1	85.46	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	KeBioLM	F1	82	—	Unverified
2	BLSTM-CNN-Char (SparkNLP)	F1	81.29	—	Unverified
3	Spark NLP	F1	81.29	—	Unverified
4	BINDER	F1	80.3	—	Unverified
5	BioMobileBERT	F1	80.13	—	Unverified
6	BioLinkBERT (large)	F1	80.06	—	Unverified
7	DistilBioBERT	F1	79.97	—	Unverified
8	CompactBioBERT	F1	79.88	—	Unverified
9	BioDistilBERT	F1	79.1	—	Unverified
10	PubMedBERT uncased	F1	79.1	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	BINDER	F1	91.9	—	Unverified
2	ConNER	F1	91.3	—	Unverified
3	CL-L2	F1	90.99	—	Unverified
4	aimped	F1	90.95	—	Unverified
5	BertForTokenClassification (Spark NLP)	F1	90.89	—	Unverified
6	BioLinkBERT (large)	F1	90.22	—	Unverified
7	ELECTRAMed	F1	90.03	—	Unverified
8	BLSTM-CNN-Char (SparkNLP)	F1	89.73	—	Unverified
9	Spark NLP	F1	89.73	—	Unverified
10	UniNER-7B	F1	89.34	—	Unverified