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

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 1901–1925 of 2874 papers

Title	Date	Tasks	Status
Industry Scale Semi-Supervised Learning for Natural Language Understanding	Mar 29, 2021	intent-classificationIntent Classification	—Unverified
InferNER: an attentive model leveraging the sentence-level information for Named Entity Recognition in Microblogs	Apr 18, 2021	named-entity-recognitionNamed Entity Recognition	—Unverified
Inferring Implicit Causal Relationships in Biomedical Literature	Aug 1, 2016	Drug DiscoveryNamed Entity Recognition (NER)	—Unverified
Inflection-Tolerant Ontology-Based Named Entity Recognition for Real-Time Applications	Dec 5, 2018	named-entity-recognitionNamed Entity Recognition	—Unverified
Inforex --- a collaborative system for text corpora annotation and analysis	Sep 1, 2017	Named Entity Recognition (NER)Word Sense Disambiguation	—Unverified
Inforex -- a web-based tool for text corpus management and semantic annotation	May 1, 2012	ManagementNamed Entity Recognition (NER)	—Unverified
Information Extraction from German Patient Records via Hybrid Parsing and Relation Extraction Strategies	May 1, 2014	ChunkingMedical Diagnosis	—Unverified
Information Extraction in Domain and Generic Documents: Findings from Heuristic-based and Data-driven Approaches	Jun 30, 2023	named-entity-recognitionNamed Entity Recognition	—Unverified
TINKER: A framework for Open source Cyberthreat Intelligence	Feb 10, 2021	Information RetrievalIntrusion Detection	—Unverified
Infrrd.ai at SemEval-2022 Task 11: A system for named entity recognition using data augmentation, transformer-based sequence labeling model, and EnsembleCRF	Jul 1, 2022	Data AugmentationLanguage Modeling	—Unverified
Initial Explorations on using CRFs for Turkish Named Entity Recognition	Dec 1, 2012	named-entity-recognitionNamed Entity Recognition	—Unverified
Injecting Categorical Labels and Syntactic Information into Biomedical NER	Nov 6, 2023	named-entity-recognitionNamed Entity Recognition	—Unverified
In Search of Meaning: Lessons, Resources and Next Steps for Computational Analysis of Financial Discourse	Mar 28, 2019	named-entity-recognitionNamed Entity Recognition	—Unverified
Inspire the Large Language Model by External Knowledge on BioMedical Named Entity Recognition	Sep 21, 2023	Language ModelingLanguage Modelling	—Unverified
Integrated Tools for Query-driven Development of Light-weight Ontologies and Information Extraction Components	Aug 1, 2014	Domain AdaptationNamed Entity Recognition (NER)	—Unverified
Integrating Boundary Assembling into a DNN Framework for Named Entity Recognition in Chinese Social Media Text	Feb 27, 2020	Boundary DetectionChinese Word Segmentation	—Unverified
Integrating Deep Learning with Logic Fusion for Information Extraction	Dec 6, 2019	Deep LearningFeature Engineering	—Unverified
Integrating Dictionary Feature into A Deep Learning Model for Disease Named Entity Recognition	Nov 5, 2019	Machine Translationnamed-entity-recognition	—Unverified
Integration of Automatic Sentence Segmentation and Lexical Analysis of Ancient Chinese based on BiLSTM-CRF Model	May 1, 2020	Lexical Analysisnamed-entity-recognition	—Unverified
Interpretability Analysis for Named Entity Recognition to Understand System Predictions and How They Can Improve	Apr 9, 2020	named-entity-recognitionNamed Entity Recognition	—Unverified
Intriguing Properties of Compression on Multilingual Models	Nov 4, 2022	named-entity-recognitionNamed Entity Recognition	—Unverified
Intrinsic Evaluation of Word Vectors Fails to Predict Extrinsic Performance	Aug 1, 2016	Named Entity Recognition (NER)Part-Of-Speech Tagging	—Unverified
Intrinsic Evaluations of Word Embeddings: What Can We Do Better?	Aug 1, 2016	Named Entity Recognition (NER)Semantic Role Labeling	—Unverified
Introducing the Hidden Neural Markov Chain framework	Feb 17, 2021	Chunkingnamed-entity-recognition	—Unverified
Investigating Different Syntactic Context Types and Context Representations for Learning Word Embeddings	Sep 1, 2017	ChunkingLearning Word Embeddings	—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