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 1651–1675 of 2874 papers

Title	Date	Tasks	Status
Multilingual is not enough: BERT for Finnish	Dec 15, 2019	Dependency Parsingnamed-entity-recognition	CodeCode Available
Robust Named Entity Recognition with Truecasing Pretraining	Dec 15, 2019	named-entity-recognitionNamed Entity Recognition	—Unverified
A Comparison of Architectures and Pretraining Methods for Contextualized Multilingual Word Embeddings	Dec 15, 2019	Multilingual Word Embeddingsnamed-entity-recognition	—Unverified
Extracting clinical concepts from user queries	Dec 12, 2019	Clinical Concept Extractionnamed-entity-recognition	—Unverified
Integrating Deep Learning with Logic Fusion for Information Extraction	Dec 6, 2019	Deep LearningFeature Engineering	—Unverified
Design and implementation of an open source Greek POS Tagger and Entity Recognizer using spaCy	Dec 5, 2019	named-entity-recognitionNamed Entity Recognition	—Unverified
Fast Intent Classification for Spoken Language Understanding	Dec 3, 2019	ClassificationDecision Making	CodeCode Available
HAMNER: Headword Amplified Multi-span Distantly Supervised Method for Domain Specific Named Entity Recognition	Dec 3, 2019	Boundary Detectionnamed-entity-recognition	—Unverified
A Primal Dual Formulation For Deep Learning With Constraints	Dec 1, 2019	Deep LearningEntity Typing	CodeCode Available
hauWE: Hausa Words Embedding for Natural Language Processing	Nov 25, 2019	Machine Translationnamed-entity-recognition	—Unverified
ScienceExamCER: A High-Density Fine-Grained Science-Domain Corpus for Common Entity Recognition	Nov 24, 2019	ClassificationGeneral Classification	—Unverified
Zero-Resource Cross-Lingual Named Entity Recognition	Nov 22, 2019	Cross-Lingual NERCross-Lingual Transfer	CodeCode Available
Global Health Monitor: A Web-based System for Detecting and Mapping Infectious Diseases	Nov 21, 2019	named-entity-recognitionNamed Entity Recognition	—Unverified
Towards Lingua Franca Named Entity Recognition with BERT	Nov 19, 2019	Cross-Lingual NERCross-Lingual Transfer	—Unverified
On the Vietnamese Name Entity Recognition: A Deep Learning Method Approach	Nov 18, 2019	ArticlesDeep Learning	—Unverified
Using Error Decay Prediction to Overcome Practical Issues of Deep Active Learning for Named Entity Recognition	Nov 17, 2019	Active Learningnamed-entity-recognition	—Unverified
Error Analysis for Vietnamese Named Entity Recognition on Deep Neural Network Models	Nov 17, 2019	named-entity-recognitionNamed Entity Recognition	—Unverified
Enhanced Meta-Learning for Cross-lingual Named Entity Recognition with Minimal Resources	Nov 14, 2019	Cross-Lingual NERCross-Lingual Transfer	CodeCode Available
Robustness to Capitalization Errors in Named Entity Recognition	Nov 13, 2019	Data Augmentationnamed-entity-recognition	—Unverified
CamemBERT: a Tasty French Language Model	Nov 10, 2019	Dependency ParsingLanguage Modeling	CodeCode Available
Knowledge Guided Named Entity Recognition for BioMedical Text	Nov 10, 2019	named-entity-recognitionNamed Entity Recognition	—Unverified
Generalizing Natural Language Analysis through Span-relation Representations	Nov 10, 2019	Aspect-Based Sentiment AnalysisAspect-Based Sentiment Analysis (ABSA)	CodeCode Available
SEPT: Improving Scientific Named Entity Recognition with Span Representation	Nov 8, 2019	named-entity-recognitionNamed Entity Recognition	—Unverified
Porous Lattice-based Transformer Encoder for Chinese NER	Nov 7, 2019	Chinese Named Entity RecognitionGPU	CodeCode Available
Dice Loss for Data-imbalanced NLP Tasks	Nov 7, 2019	Chinese Named Entity RecognitionMachine Reading Comprehension	CodeCode Available

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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