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Named Entity Recognition (NER)

672 평가 기록 114 datasets

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

<span style="color:grey; opacity: 0.6">( Image credit: Zalando )</span>

개요는 각 항목의 일부입니다. 위 탭에서 전체 기록을 페이지별로 탐색할 수 있습니다.

벤치마크

Papers with Code 아카이브의 데이터셋별 기록 예시입니다. 평가 조건과 지표 방향이 검증되지 않아 순위를 의미하지 않습니다.

Dataset기록된 모델 예시MetricPaperCode
ACE + document-context
F1: 94.6
논문 코드
BERT-MRC+DSC
F1: 92.07
논문 코드
PIQN
F1: 81.77
논문 코드
BioBERT
F1: 89.71
논문 코드
BINDER
F1: 89.5
논문 코드
PromptNER [RoBERTa-large]
F1: 88.72
논문 코드
CL-KL
F1: 60.45
논문 코드
BERT-MRC+DSC
F1: 96.72
논문 코드
Ours: cross-sentence ALB
F1: 90.9
논문 코드
BERT-CRF (Replicated in AdaSeq)
F1: 72.77
논문 코드
KeBioLM
F1: 82.0
논문 코드
BINDER
F1: 91.9
논문 코드

데이터셋

114개
CoNLL 2003 (English)Ontonotes v5 (English)GENIANCBI-diseaseACE 2005ACE 2004WNUT 2017MSRAACE 2005Weibo NERJNLPBABC5CDR

논문

라이브러리

Papers with Code 리더보드 row에 연결된 구현 저장소입니다.

github.com/JohnSnowLabs/spark-nlp-workshop/blob/master/tutorials/Certification_Trainings/Healthcare/1.4.Biomedical_NER_SparkNLP_paper_reproduce.ipynb 1 논문
dagshub.com/Dean/BioBERT-DAGsHub 1 논문
github.com/2024-MindSpore-1/Code2/tree/main/model-1/camembert 1 논문
github.com/Alibaba-NLP/CLNER 1 논문
github.com/anaishoareau/french_preprocessing 1 논문
github.com/ardakdemir/my_bert_ner 1 논문
github.com/bourrel/French-News-Clustering 1 논문
github.com/charles9n/bert-sklearn 1 논문

하위 태스크

NN Nested Named Entity Recognition 6 데이터셋 · 85 rows CN Chinese Named Entity Recognition 7 데이터셋 · 72 rows FN Few-shot NER 4 데이터셋 · 28 rows MN Multi-modal Named Entity Recognition 5 데이터셋 · 22 rows ZN Zero-shot Named Entity Recognition (NER) 4 데이터셋 · 10 rows MN Medical Named Entity Recognition 2 데이터셋 · 5 rows N NER 6 데이터셋 · 4 rows NE Named Entity Recognition In Vietnamese 2 데이터셋 · 4 rows SC Scientific Concept Extraction 1 데이터셋 · 2 rows CN Cross-Domain Named Entity Recognition 1 데이터셋 · 1 rows MN Multi-Grained Named Entity Recognition 0 데이터셋 · 0 rows MN Multilingual Named Entity Recognition 0 데이터셋 · 0 rows