Papers with Code 아카이브
Named Entity Recognition (NER)
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- 평가표
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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/deepmipt/Slavic-BERT-NER
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/deepmipt/bert/tree/feat/multi_gpu
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/deepmipt/ner
https://github.com/deepset-ai/FARM
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/demdecuong/vihealthbert
https://github.com/deping-1/2019-false-news-detection-challenge
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/derekchen14/mixture_soft_prompts
https://github.com/derronxu/sparsebert
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/determined22/zh-ner-tf
https://github.com/devJWSong/bert-crf-entity-recognition-pytorch
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/devkotasabin/EBM-NLP
https://github.com/dhiraa/tener
TENER: Adapting Transformer Encoder for Named Entity Recognition
https://github.com/dhlee347/pytorchic-bert
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/diabhaque/Sixth-Sense
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/diffbot/knowledge-net
Entity, Relation, and Event Extraction with Contextualized Span Representations
https://github.com/dispink/xpt
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/dmis-lab/bern
BioBERT: a pre-trained biomedical language representation model for biomedical text mining
https://github.com/dmlc/gluon-nlp
https://github.com/dnanhkhoa/WNUT-2020
https://github.com/dreamgonfly/BERT-pytorch
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/drgriffis/knn-embedding
Second-Order Word Embeddings from Nearest Neighbor Topological Features
https://github.com/duyunshu/bert-sentiment-analysis
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/dzqjorking/transpose
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/eagle705/bert
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/eaishwa/quora-ques-pair-similarity
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/edchengg/transfusion
Frustratingly Easy Label Projection for Cross-lingual Transfer
https://github.com/elenalenaelena/machine-learning-viz
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/enod/arxiv-nlp-notes
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/epcpu/deep-nlp-links
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/epfml/collaborative-attention
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/epwalsh/pytorch-crf
https://github.com/eric-erki/decaNLP
The Natural Language Decathlon: Multitask Learning as Question Answering
https://github.com/ericperfect/Bert_Position_BiLSTM_Attention_CRF_LSTMDecoder
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/eunseo1092/Graduation_project
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
https://github.com/evtaktasheva/dependency_extraction
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.