https://github.com/microsoft/vert-papers/tree/master/papers/Meta-Cross
공식 코드Enhanced Meta-Learning for Cross-lingual Named Entity Recognition with Minimal Resources
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/microsoft/vert-papers/tree/master/papers/SingleMulti-TS
공식 코드https://github.com/microsoft/vert-papers/tree/master/papers/UniTrans
공식 코드https://github.com/microsoft/xtreme-distil-transformers
공식 코드XtremeDistilTransformers: Task Transfer for Task-agnostic Distillation
https://github.com/milangritta/Pragmatic-Guide-to-Geoparsing-Evaluation
공식 코드https://github.com/mingdachen/vsl
공식 코드Variational Sequential Labelers for Semi-Supervised Learning
https://github.com/minghao-wu/CRF-AE
공식 코드Evaluating the Utility of Hand-crafted Features in Sequence Labelling
https://github.com/mlrs/bertu
공식 코드https://github.com/mnamysl/nat-acl2020
공식 코드NAT: Noise-Aware Training for Robust Neural Sequence Labeling
https://github.com/modelscope/AdaSeq/tree/master/examples/RaNER
공식 코드Improving Named Entity Recognition by External Context Retrieving and Cooperative Learning
https://github.com/modelscope/AdaSeq/tree/master/examples/babert
공식 코드Unsupervised Boundary-Aware Language Model Pretraining for Chinese Sequence Labeling
https://github.com/modelscope/adaseq
공식 코드Improving Named Entity Recognition by External Context Retrieving and Cooperative Learning
https://github.com/mohammadKhalifa/zero-shot-arabic-dialects
공식 코드https://github.com/moncefbenaicha/spoken-ner
공식 코드Leveraging Cross-Lingual Transfer Learning in Spoken Named Entity Recognition Systems
https://github.com/monikkinom/ner-lstm
공식 코드Towards Deep Learning in Hindi NER: An approach to tackle the Labelled Data Scarcity
https://github.com/mozzitastebitter/medjex
공식 코드https://github.com/mushfiqur11/tokenfreetransfer
공식 코드To token or not to token: A Comparative Study of Text Representations for Cross-Lingual Transfer
https://github.com/mxhofer/Named-Entity-Recognition-BidirectionalLSTM-CNN-CoNLL
공식 코드Few-shot Learning for Named Entity Recognition in Medical Text
https://github.com/mykelismyname/mslm
공식 코드https://github.com/naiveneuron/wikigoldsk
공식 코드https://github.com/napsternxg/NER_bias
공식 코드https://github.com/nardien/kala
공식 코드https://github.com/nasimisu/truth-discovery-in-sequence-labels-from-crowds
공식 코드https://github.com/naver/biobert-pretrained
공식 코드BioBERT: a pre-trained biomedical language representation model for biomedical text mining
https://github.com/ncbi-nlp/BLUE_Benchmark
공식 코드https://github.com/ncbi-nlp/NCBI_BERT
공식 코드https://github.com/ncbi-nlp/bluebert
공식 코드An Empirical Study of Multi-Task Learning on BERT for Biomedical Text Mining
https://github.com/ncbi/aioner
공식 코드AIONER: All-in-one scheme-based biomedical named entity recognition using deep learning
https://github.com/ndionysus/twitter-cyberthreat-detection
공식 코드Cyberthreat Detection from Twitter using Deep Neural Networks
https://github.com/nerel-ds/nerel
공식 코드NEREL: A Russian Dataset with Nested Named Entities, Relations and Events
https://github.com/neukg/MultiIE
공식 코드https://github.com/neukg/techgpt-2.0
공식 코드TechGPT-2.0: A large language model project to solve the task of knowledge graph construction
https://github.com/neulab/InterpretEval
공식 코드Interpretable Multi-dataset Evaluation for Named Entity Recognition
https://github.com/neulab/cmu-multinlp
공식 코드Generalizing Natural Language Analysis through Span-relation Representations
https://github.com/neulab/soft-gazetteers
공식 코드https://github.com/neulab/spanner
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.