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/jinlanfu/polyglot_prompt
공식 코드https://github.com/jinpeng01/hgn
공식 코드https://github.com/jinyuanli0012/pgim
공식 코드https://github.com/jouniluoma/bert-ner-cmv
공식 코드Exploring Cross-sentence Contexts for Named Entity Recognition with BERT
https://github.com/juand-r/entity-recognition-datasets
공식 코드Do "English" Named Entity Recognizers Work Well on Global Englishes?
https://github.com/juditacs/hubert_eval
공식 코드https://github.com/juditacs/subword-choice
공식 코드https://github.com/juditacs/uralic_eval
공식 코드Evaluating Transferability of BERT Models on Uralic Languages
https://github.com/junchenzhi/logic-lncl
공식 코드https://github.com/juntaoy/biaffine-ner
공식 코드https://github.com/juntaoy/dali-md
공식 코드https://github.com/junwang4/linking-health-news-to-pubmed
공식 코드https://github.com/justinpayan/stackoverflowner-ns
공식 코드Towards Realistic Single-Task Continuous Learning Research for NER
https://github.com/justinphan3110/SciFive
공식 코드SciFive: a text-to-text transformer model for biomedical literature
https://github.com/jwallat/knowledge-probing
공식 코드BERTnesia: Investigating the capture and forgetting of knowledge in BERT
https://github.com/jxmorris12/unsupervised-text-deidentification
공식 코드https://github.com/jyz99/cmner
공식 코드CMNER: A Chinese Multimodal NER Dataset based on Social Media
https://github.com/jzbjyb/SpanRel
공식 코드Generalizing Natural Language Analysis through Span-relation Representations
https://github.com/kaeflint/GTI
공식 코드Gated Task Interaction Framework for Multi-task Sequence Tagging
https://github.com/kalawinka/season
공식 코드https://github.com/kangISU/Conf-MPU-DS-NER
공식 코드https://github.com/katotakuma0501/Fine-grained-NER-models
공식 코드https://github.com/katzurik/neretrieve
공식 코드NERetrieve: Dataset for Next Generation Named Entity Recognition and Retrieval
https://github.com/kawatami/dner
공식 코드https://github.com/keenon/lense
공식 코드https://github.com/kentonmurray/arabicdetokenizer
공식 코드https://github.com/kimiyoung/transfer
공식 코드Transfer Learning for Sequence Tagging with Hierarchical Recurrent Networks
https://github.com/klimzaporojets/DWIE
공식 코드DWIE: an entity-centric dataset for multi-task document-level information extraction
https://github.com/klimzaporojets/e2e-kb-ie
공식 코드https://github.com/knowledge-computing/geolm
공식 코드GeoLM: Empowering Language Models for Geospatially Grounded Language Understanding
https://github.com/knowledgeresearch/kaner
공식 코드Rethinking the Value of Gazetteer in Chinese Named Entity Recognition
https://github.com/komeijiforce/x-ner
공식 코드Less than One-shot: Named Entity Recognition via Extremely Weak Supervision
https://github.com/konstantinjdobler/focus
공식 코드FOCUS: Effective Embedding Initialization for Monolingual Specialization of Multilingual Models
https://github.com/kormilitzin/med7
공식 코드Med7: a transferable clinical natural language processing model for electronic health records
https://github.com/krishnap25/casimir
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.