https://github.com/vsymbol/CUTIE
공식 코드CUTIE: Learning to Understand Documents with Convolutional Universal Text Information Extractor
Papers with Code 아카이브
Named Entity Recognition (NER)
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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>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/wangpeiyi9979/esd
공식 코드An Enhanced Span-based Decomposition Method for Few-Shot Sequence Labeling
https://github.com/wasiahmad/Syntax-MBERT
공식 코드Syntax-augmented Multilingual BERT for Cross-lingual Transfer
https://github.com/wataruhashimoto52/ner_da_uncertainty
공식 코드Are Data Augmentation Methods in Named Entity Recognition Applicable for Uncertainty Estimation?
https://github.com/webspellchecker/unlp-2023-shared-task
공식 코드RedPenNet for Grammatical Error Correction: Outputs to Tokens, Attentions to Spans
https://github.com/wglab/bioformer
공식 코드Bioformer: an efficient transformer language model for biomedical text mining
https://github.com/whoisjones/familarity
공식 코드https://github.com/wietsedv/bertje
공식 코드https://github.com/wjx-git/deptriggerner
공식 코드Low-Resource Named Entity Recognition Based on Multi-hop Dependency Trigger
https://github.com/wonjininfo/CollaboNet
공식 코드CollaboNet: collaboration of deep neural networks for biomedical named entity recognition
https://github.com/wuyuefei3/BR
공식 코드A Boundary Regression Model for Nested Named Entity Recognition
https://github.com/wzh-nlp/pltr
공식 코드Generalizing Few-Shot Named Entity Recognizers to Unseen Domains with Type-Related Features
https://github.com/wzh-nlp/www25-cmas
공식 코드A Cooperative Multi-Agent Framework for Zero-Shot Named Entity Recognition
https://github.com/wzhouad/NLL-IE
공식 코드Learning from Noisy Labels for Entity-Centric Information Extraction
https://github.com/xhuang28/NewBioNer
공식 코드https://github.com/xianjun-yang/pcmsp
공식 코드https://github.com/xmb-cipher/fofe-ner
공식 코드A FOFE-based Local Detection Approach for Named Entity Recognition and Mention Detection
https://github.com/xplip/pixel
공식 코드https://github.com/xuandongzhao/drw
공식 코드Distillation-Resistant Watermarking for Model Protection in NLP
https://github.com/xuuuluuu/SynLSTM-for-NER
공식 코드https://github.com/xuuuluuu/ds_ner
공식 코드Better Sampling of Negatives for Distantly Supervised Named Entity Recognition
https://github.com/yahshibu/nested-ner-tacl2020
공식 코드Nested Named Entity Recognition via Second-best Sequence Learning and Decoding
https://github.com/yahshibu/nested-ner-tacl2020-flair
공식 코드Nested Named Entity Recognition via Second-best Sequence Learning and Decoding
https://github.com/yahshibu/nested-ner-tacl2020-transformers
공식 코드Nested Named Entity Recognition via Second-best Sequence Learning and Decoding
https://github.com/yale-lily/r2d2
공식 코드https://github.com/yanzhh/hgere
공식 코드Joint Entity and Relation Extraction with Span Pruning and Hypergraph Neural Networks
https://github.com/yaswanth-iitkgp/depnecti
공식 코드DepNeCTI: Dependency-based Nested Compound Type Identification for Sanskrit
https://github.com/yhcc/BARTNER
공식 코드https://github.com/yhcc/cnn_nested_ner
공식 코드An Embarrassingly Easy but Strong Baseline for Nested Named Entity Recognition
https://github.com/yhydhx/chatgpt-api
공식 코드https://github.com/yibowang214/multiner
공식 코드Named Entity Recognition via Machine Reading Comprehension: A Multi-Task Learning Approach
https://github.com/yilunzhu/splice
공식 코드SPLICE: A Singleton-Enhanced PipeLIne for Coreference REsolution
https://github.com/yinghao-li/gno-ie
공식 코드https://github.com/ylab-open/mets-cov
공식 코드METS-CoV: A Dataset of Medical Entity and Targeted Sentiment on COVID-19 Related Tweets
https://github.com/ymcui/Chinese-BERT-wwm
공식 코드https://github.com/ynchuang/discoverpath
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.