https://github.com/google-research/bert
공식 코드BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
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/graal-research/risc
공식 코드RISC: Generating Realistic Synthetic Bilingual Insurance Contract
https://github.com/gt-salt/guided-adversarial-augmentation
공식 코드https://github.com/gtfintechlab/finer
공식 코드FiNER-ORD: Financial Named Entity Recognition Open Research Dataset
https://github.com/gtfintechlab/finer-ord
공식 코드FiNER-ORD: Financial Named Entity Recognition Open Research Dataset
https://github.com/guanqun-yang/fewvulnerability
공식 코드https://github.com/guanrunwei/findvehicle
공식 코드https://github.com/guanrunwei/vehiclefinder-ctim
공식 코드https://github.com/gyeongmin47/kochet
공식 코드KoCHET: a Korean Cultural Heritage corpus for Entity-related Tasks
https://github.com/h2oai/h2o-llmstudio
공식 코드https://github.com/hamlaertes/emnlp_2022_reconciliation
공식 코드https://github.com/haneul-yoo/hue
공식 코드HUE: Pretrained Model and Dataset for Understanding Hanja Documents of Ancient Korea
https://github.com/harshpatel1014/BioNerFlair
공식 코드BioNerFlair: biomedical named entity recognition using flair embedding and sequence tagger
https://github.com/harshshredding/smm4h-2022-social-dis-ner-submission
공식 코드https://github.com/hccngu/metnet
공식 코드Meta-Learning Triplet Network with Adaptive Margins for Few-Shot Named Entity Recognition
https://github.com/he159ok/uncseqlabeling_slpn
공식 코드Uncertainty Estimation on Sequential Labeling via Uncertainty Transmission
https://github.com/healx/biomed-slot-filling
공식 코드https://github.com/hecta-uom/ensemble-ner
공식 코드https://github.com/hecta-uom/label-to-text-transformer
공식 코드Generating Medical Prescriptions with Conditional Transformer
https://github.com/hecta-uom/synthetic4health
공식 코드Synthetic4Health: Generating Annotated Synthetic Clinical Letters
https://github.com/herandy/Skill-LLM
공식 코드Skill-LLM: Repurposing General-Purpose LLMs for Skill Extraction
https://github.com/hillary-ngai/doctor_xavier
공식 코드Doctor XAvIer: Explainable Diagnosis on Physician-Patient Dialogues and XAI Evaluation
https://github.com/him1411/edgar10q-dataset
공식 코드https://github.com/hiroki13/instance-based-ner
공식 코드Instance-Based Learning of Span Representations: A Case Study through Named Entity Recognition
https://github.com/hitz-zentroa/gollie
공식 코드GoLLIE: Annotation Guidelines improve Zero-Shot Information-Extraction
https://github.com/hjzhao73/multigenre-chinesenovel
공식 코드A Corpus for Named Entity Recognition in Chinese Novels with Multi-genres
https://github.com/hkust-knowcomp/bekg
공식 코드https://github.com/hkust-lib-ds/P001-PUBLIC_Chinese-NER-Tool
공식 코드https://github.com/hlt-mt/fbk-fairseq
공식 코드https://github.com/hltcoe/gazetteer-collection
공식 코드https://github.com/honghanhh/ner-combining-contextual-and-global-features
공식 코드Named entity recognition architecture combining contextual and global features
https://github.com/hooshvare/parsbert
공식 코드ParsBERT: Transformer-based Model for Persian Language Understanding
https://github.com/houking-can/RDANER
공식 코드A Robust and Domain-Adaptive Approach for Low-Resource Named Entity Recognition
https://github.com/hriaz17/ellen
공식 코드ELLEN: Extremely Lightly Supervised Learning For Efficient Named Entity Recognition
https://github.com/huawei-noah/Pretrained-Language-Model
공식 코드https://github.com/huertas97/xx_ner_wordcamouflage
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.