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 101–150 of 2874 papers

TitleStatusHype
Synthetic4Health: Generating Annotated Synthetic Clinical LettersCode0
WhisperNER: Unified Open Named Entity and Speech RecognitionCode3
SubRegWeigh: Effective and Efficient Annotation Weighing with Subword RegularizationCode0
Preserving Empirical Probabilities in BERT for Small-sample Clinical Entity Recognition—0
LSTM Recurrent Neural Networks for Cybersecurity Named Entity Recognition—0
Evaluating Named Entity Recognition Using Few-Shot Prompting with Large Language ModelsCode1
Investigating LLM Applications in E-Commerce—0
CLLMFS: A Contrastive Learning enhanced Large Language Model Framework for Few-Shot Named Entity Recognition—0
LLMs are not Zero-Shot Reasoners for Biomedical Information Extraction—0
AttackER: Towards Enhancing Cyber-Attack Attribution with a Named Entity Recognition Dataset—0
mucAI at WojoodNER 2024: Arabic Named Entity Recognition with Nearest Neighbor Search—0
Enhancing Supply Chain Visibility with Knowledge Graphs and Large Language Models—0
Comparative Analysis of Encoder-Based NER and Large Language Models for Skill Extraction from Russian Job Vacancies—0
Learning Robust Named Entity Recognizers From Noisy Data With Retrieval Augmentation—0
Developing a Reliable, Fast, General-Purpose Hallucination Detection and Mitigation Service—0
MMM: Multilingual Mutual Reinforcement Effect Mix Datasets & Test with Open-domain Information Extraction Large Language Models—0
WojoodNER 2024: The Second Arabic Named Entity Recognition Shared Task—0
FsPONER: Few-shot Prompt Optimization for Named Entity Recognition in Domain-specific ScenariosCode0
TokenVerse: Towards Unifying Speech and NLP Tasks via Transducer-based ASRCode0
Entity Decomposition with Filtering: A Zero-Shot Clinical Named Entity Recognition Framework—0
Are Data Augmentation Methods in Named Entity Recognition Applicable for Uncertainty Estimation?Code0
Bridging the Gap: Transfer Learning from English PLMs to Malaysian English—0
Adapting Multilingual LLMs to Low-Resource Languages with Knowledge Graphs via AdaptersCode0
Show Less, Instruct More: Enriching Prompts with Definitions and Guidelines for Zero-Shot NER—0
Large Language Models Struggle in Token-Level Clinical Named Entity RecognitionCode0
BioMNER: A Dataset for Biomedical Method Entity Recognition—0
TocBERT: Medical Document Structure Extraction Using Bidirectional Transformers—0
Annotation Errors and NER: A Study with OntoNotes 5.0—0
Retrieval Augmented Instruction Tuning for Open NER with Large Language ModelsCode1
Transformer-based Named Entity Recognition with Combined Data Representation—0
In-Context Learning on a Budget: A Case Study in Token Classification—0
Medical Spoken Named Entity RecognitionCode0
Beyond Boundaries: Learning a Universal Entity Taxonomy across Datasets and Languages for Open Named Entity RecognitionCode1
Improving Autoregressive Training with Dynamic Oracles—0
Curating Grounded Synthetic Data with Global Perspectives for Equitable AI—0
Fighting Against the Repetitive Training and Sample Dependency Problem in Few-shot Named Entity Recognition—0
DeviceBERT: Applied Transfer Learning With Targeted Annotations and Vocabulary Enrichment to Identify Medical Device and Component Terminology in FDA Recall Summaries—0
llmNER: (Zero|Few)-Shot Named Entity Recognition, Exploiting the Power of Large Language Models—0
Assessing the Performance of Chinese Open Source Large Language Models in Information Extraction Tasks—0
Synergizing Unsupervised and Supervised Learning: A Hybrid Approach for Accurate Natural Language Task Modeling—0
Improving Pseudo Labels with Global-Local Denoising Framework for Cross-lingual Named Entity RecognitionCode1
GAMedX: Generative AI-based Medical Entity Data Extractor Using Large Language Models—0
CPE-Identifier: Automated CPE identification and CVE summaries annotation with Deep Learning and NLP—0
MSNER: A Multilingual Speech Dataset for Named Entity Recognition—0
CoNECo: A corpus for named entity recognition and normalization of protein complexes—0
Evaluation of large language model performance on the Biomedical Language Understanding and Reasoning Benchmark—0
KnowledgeHub: An end-to-end Tool for Assisted Scientific Discovery—0
Unveiling Social Media Comments with a Novel Named Entity Recognition System for Identity Groups—0
NoiseBench: Benchmarking the Impact of Real Label Noise on Named Entity RecognitionCode0
Reddit-Impacts: A Named Entity Recognition Dataset for Analyzing Clinical and Social Effects of Substance Use Derived from Social Media—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
4BLSTM-CNN-Char (SparkNLP)F189.13—Unverified
5Spark NLPF189.13—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
8Spark NLPF189.73—Unverified
9BLSTM-CNN-Char (SparkNLP)F189.73—Unverified
10UniNER-7BF189.34—Unverified