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 651–675 of 2874 papers

Title	Date	Tasks	Status
A Survey on Arabic Named Entity Recognition: Past, Recent Advances, and Future Trends	Feb 7, 2023	Feature EngineeringLanguage Modeling	—Unverified
A Survey of Named Entity Recognition in Assamese and other Indian Languages	Jul 9, 2014	Document SummarizationMachine Translation	—Unverified
A Multi-Strategy Approach for Location Mining in Tweets: AUT NLP Group Entry for ALTA-2014 Shared Task	Nov 1, 2014	named-entity-recognitionNamed Entity Recognition	—Unverified
A Survey of Arabic Named Entity Recognition and Classification	Jun 1, 2014	ClassificationGeneral Classification	—Unverified
A multimodal deep learning approach for named entity recognition from social media	Jan 19, 2020	Information RetrievalMultimodal Deep Learning	—Unverified
A Deep Learning-Based System for PharmaCoNER	Nov 1, 2019	Deep LearningGeneral Classification	—Unverified
Cross-Lingual Named Entity Recognition via Wikification	Aug 1, 2016	Entity LinkingInformation Retrieval	—Unverified
Cross-Lingual Part-of-Speech Tagging through Ambiguous Learning	Oct 1, 2014	Cross-Lingual TransferNamed Entity Recognition (NER)	—Unverified
Cross Script Hindi English NER Corpus from Wikipedia	Oct 8, 2018	named-entity-recognitionNamed Entity Recognition	—Unverified
A Survey of Adversarial Defences and Robustness in NLP	Mar 12, 2022	Adversarial Defensenamed-entity-recognition	—Unverified
ASU: An Experimental Study on Applying Deep Learning in Twitter Named Entity Recognition.	Dec 1, 2016	Entity Extraction using GANnamed-entity-recognition	—Unverified
A Multilingual Evaluation of NER Robustness to Adversarial Inputs	May 30, 2023	named-entity-recognitionNamed Entity Recognition	—Unverified
A Study on the Integration of Pre-trained SSL, ASR, LM and SLU Models for Spoken Language Understanding	Nov 10, 2022	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
A Study of the Importance of External Knowledge in the Named Entity Recognition Task	Jul 1, 2018	named-entity-recognitionNamed Entity Recognition	—Unverified
A Multilingual Entity Linker Using PageRank and Semantic Graphs	May 1, 2017	Entity LinkingNamed Entity Recognition (NER)	—Unverified
A Deep Learning Approach to Integrate Human-Level Understanding in a Chatbot	Dec 31, 2021	Chatbotintent-classification	—Unverified
A Study of Recent Contributions on Information Extraction	Mar 15, 2018	BIG-bench Machine Learningnamed-entity-recognition	—Unverified
A Multi-Gate Encoder for Joint Entity and Relation Extraction	Oct 1, 2022	Joint Entity and Relation Extractionnamed-entity-recognition	—Unverified
Cross-Lingual Ability of Multilingual BERT: An Empirical Study	Dec 17, 2019	named-entity-recognitionNamed Entity Recognition	—Unverified
A multi-constraint structured hinge loss for named-entity recognition	Apr 1, 2019	named-entity-recognitionNamed Entity Recognition	—Unverified
Assorted, Archetypal and Annotated Two Million (3A2M) Cooking Recipes Dataset based on Active Learning	Mar 27, 2023	Active LearningGenre classification	—Unverified
A Deep Learning approach for Hindi Named Entity Recognition	Nov 5, 2019	Deep Learningnamed-entity-recognition	—Unverified
Cross-lingual alignments of ELMo contextual embeddings	Jun 30, 2021	Dependency Parsingnamed-entity-recognition	—Unverified
Cross-lingual alignment transfer: a chicken-and-egg story?	Jun 1, 2016	Cross-Lingual TransferDependency Parsing	—Unverified
Assessment of DistilBERT performance on Named Entity Recognition task for the detection of Protected Health Information and medical concepts	Nov 1, 2020	named-entity-recognitionNamed Entity Recognition	—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	BLSTM-CNN-Char (SparkNLP)	F1	89.13	—	Unverified
5	Spark NLP	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	Spark NLP	F1	89.73	—	Unverified
9	BLSTM-CNN-Char (SparkNLP)	F1	89.73	—	Unverified
10	UniNER-7B	F1	89.34	—	Unverified