SOTAVerified

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 651–700 of 2874 papers

TitleStatusHype
A Deep Neural Network based Approach for Entity Extraction in Code-Mixed Indian Social Media Text—0
DAMO-NLP at SemEval-2023 Task 2: A Unified Retrieval-augmented System for Multilingual Named Entity Recognition—0
A Survey on Arabic Named Entity Recognition: Past, Recent Advances, and Future Trends—0
A Survey of Named Entity Recognition in Assamese and other Indian Languages—0
A Multi-Strategy Approach for Location Mining in Tweets: AUT NLP Group Entry for ALTA-2014 Shared Task—0
A Survey of Arabic Named Entity Recognition and Classification—0
A multimodal deep learning approach for named entity recognition from social media—0
A Deep Learning-Based System for PharmaCoNER—0
DaNE: A Named Entity Resource for Danish—0
A Survey of Adversarial Defences and Robustness in NLP—0
ASU: An Experimental Study on Applying Deep Learning in Twitter Named Entity Recognition.—0
A Multilingual Evaluation of NER Robustness to Adversarial Inputs—0
A Deep Learning Approach to Integrate Human-Level Understanding in a Chatbot—0
A Multilingual Entity Linker Using PageRank and Semantic Graphs—0
Czech Text Processing with Contextual Embeddings: POS Tagging, Lemmatization, Parsing and NER—0
DaCy: A Unified Framework for Danish NLP—0
A Study of Recent Contributions on Information Extraction—0
CONTaiNER: Few-Shot Named Entity Recognition via Contrastive Learning—0
A Multi-Gate Encoder for Joint Entity and Relation Extraction—0
A multi-constraint structured hinge loss for named-entity recognition—0
Assorted, Archetypal and Annotated Two Million (3A2M) Cooking Recipes Dataset based on Active Learning—0
A Deep Learning approach for Hindi Named Entity Recognition—0
Czech Historical Named Entity Corpus v 1.0—0
DAGA: Data Augmentation with a Generation Approach for Low-resource Tagging Tasks—0
A Morpho-Syntactically Informed LSTM-CRF Model for Named Entity Recognition—0
Connecting Distant Entities with Induction through Conditional Random Fields for Named Entity Recognition: Precursor-Induced CRF—0
Assessing the Performance of Chinese Open Source Large Language Models in Information Extraction Tasks—0
CU-NLP at SemEval-2016 Task 8: AMR Parsing using LSTM-based Recurrent Neural Networks—0
Confidence penalty, annealing Gaussian noise and zoneout for biLSTM-CRF networks for named entity recognition—0
Confidence estimation of classification based on the distribution of the neural network output layer—0
Assessing multiple word embeddings for named entity recognition of professions and occupations in health-related social media—0
CoNECo: A corpus for named entity recognition and normalization of protein complexes—0
Computing Word Classes Using Spectral Clustering—0
A More Efficient Chinese Named Entity Recognition base on BERT and Syntactic Analysis—0
Assessment of DistilBERT performance on Named Entity Recognition task for the detection of Protected Health Information and medical concepts—0
Constrained Labeled Data Generation for Low-Resource Named Entity Recognition—0
Constructing a Knowledge Graph from Textual Descriptions of Software Vulnerabilities in the National Vulnerability Database—0
Constructing a Korean Named Entity Recognition Dataset for the Financial Domain using Active Learning—0
Constructing a Word Similarity Graph from Vector based Word Representation for Named Entity Recognition—0
Constructing Uyghur Name Entity Recognition System using Neural Machine Translation Tag Projection—0
A Deeper Study on Features for Named Entity Recognition—0
Curating Grounded Synthetic Data with Global Perspectives for Equitable AI—0
context2vec: Learning Generic Context Embedding with Bidirectional LSTM—0
Context-aware Adversarial Training for Name Regularity Bias in Named Entity Recognition—0
Context-aware Fine-tuning of Self-supervised Speech Models—0
A Study of the Importance of External Knowledge in the Named Entity Recognition Task—0
A Study on the Integration of Pre-trained SSL, ASR, LM and SLU Models for Spoken Language Understanding—0
Context-Sensitive Recognition for Emerging and Rare Entities—0
Contextual Characters with Segmentation Representation for Named Entity Recognition in Chinese—0
Computer Science Articles Named Entity Recognition Datasets: Survey and Our Recent Development—0
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All datasetsCoNLL 2003 (English)Ontonotes v5 (English)NCBI DiseaseWNUT 2017ACE 2005JNLPBABC5CDRGENIABC2GMBC5CDR-chemicalSLUECoNLL++

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ACE + document-contextF194.6—Unverified
2LUKE 483MF194.3—Unverified
3Co-regularized LUKEF194.22—Unverified
4LUKE + SubRegWeigh (K-means)F194.2—Unverified
5ASP+T5-3BF194.1—Unverified
6FLERT XLM-RF194.09—Unverified
7PL-MarkerF194—Unverified
8CL-KLF193.85—Unverified
9XLNet-GCNF193.82—Unverified
10RoBERTa + SubRegWeigh (K-means)F193.81—Unverified
#ModelMetricClaimedVerifiedStatus
1BERT-MRC+DSCF192.07—Unverified
2PL-MarkerF191.9—Unverified
3Baseline + BSF191.74—Unverified
4Biaffine-NERF191.3—Unverified
5BERT-MRCF191.11—Unverified
6PIQNF190.96—Unverified
7HGNF190.92—Unverified
8Syn-LSTM + BERT (wo doc-context)F190.85—Unverified
9DiffusionNERF190.66—Unverified
10W2NERF190.5—Unverified
#ModelMetricClaimedVerifiedStatus
1BioBERTF189.71—Unverified
2SpanModel + SequenceLabelingModelF189.6—Unverified
3SciFive-BaseF189.39—Unverified
4Spark NLPF189.13—Unverified
5BLSTM-CNN-Char (SparkNLP)F189.13—Unverified
6KeBioLMF189.1—Unverified
7CL-KLF188.96—Unverified
8BioKMNER + BioBERTF188.77—Unverified
9BioLinkBERT (large)F188.76—Unverified
10CompactBioBERTF188.67—Unverified
#ModelMetricClaimedVerifiedStatus
1CL-KLF160.45—Unverified
2RoBERTa + SubRegWeigh (K-means)F160.29—Unverified
3BERT-CRF (Replicated in AdaSeq)F159.69—Unverified
4RoBERTa-BiLSTM-contextF159.61—Unverified
5BERT + RegLERF158.9—Unverified
6TNER -xlm-r-largeF158.5—Unverified
7HGNF157.41—Unverified
8ASA + RoBERTaF157.3—Unverified
9BERTweetF156.5—Unverified
10MINERF154.86—Unverified
#ModelMetricClaimedVerifiedStatus
1Ours: cross-sentence ALBF190.9—Unverified
2GoLLIEF189.6—Unverified
3PromptNER [RoBERTa-large]F188.26—Unverified
4PIQNF187.42—Unverified
5PromptNER [BERT-large]F187.21—Unverified
6DiffusionNERF186.93—Unverified
7BERT-MRCF186.88—Unverified
8UniNER-7BF186.69—Unverified
9Locate and LabelF186.67—Unverified
10BoningKnifeF185.46—Unverified
#ModelMetricClaimedVerifiedStatus
1KeBioLMF182—Unverified
2BLSTM-CNN-Char (SparkNLP)F181.29—Unverified
3Spark NLPF181.29—Unverified
4BINDERF180.3—Unverified
5BioMobileBERTF180.13—Unverified
6BioLinkBERT (large)F180.06—Unverified
7DistilBioBERTF179.97—Unverified
8CompactBioBERTF179.88—Unverified
9BioDistilBERTF179.1—Unverified
10PubMedBERT uncasedF179.1—Unverified
#ModelMetricClaimedVerifiedStatus
1BINDERF191.9—Unverified
2ConNERF191.3—Unverified
3CL-L2F190.99—Unverified
4aimpedF190.95—Unverified
5BertForTokenClassification (Spark NLP)F190.89—Unverified
6BioLinkBERT (large)F190.22—Unverified
7ELECTRAMedF190.03—Unverified
8BLSTM-CNN-Char (SparkNLP)F189.73—Unverified
9Spark NLPF189.73—Unverified
10UniNER-7BF189.34—Unverified