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/yuanhy1997/partialkb-el
공식 코드Exploring Partial Knowledge Base Inference in Biomedical Entity Linking
https://github.com/yuanli95/eega-for-jmere
공식 코드https://github.com/yumeng5/roster
공식 코드https://github.com/yuzhimanhua/lm-lstm-crf
공식 코드Cross-type Biomedical Named Entity Recognition with Deep Multi-Task Learning
https://github.com/yyDing1/DS-NER
공식 코드Towards DS-NER: Unveiling and Addressing Latent Noise in Distant Annotations
https://github.com/yyding1/gner
공식 코드Rethinking Negative Instances for Generative Named Entity Recognition
https://github.com/zenanz/ChemPatentEmbeddings
공식 코드Improving Chemical Named Entity Recognition in Patents with Contextualized Word Embeddings
https://github.com/zenhjunpro/atsen
공식 코드https://github.com/zerohd4869/SLK-NER
공식 코드SLK-NER: Exploiting Second-order Lexicon Knowledge for Chinese NER
https://github.com/zhang-mozhi/promptner
공식 코드PromptNER: A Prompting Method for Few-shot Named Entity Recognition via k Nearest Neighbor Search
https://github.com/zhangsha1024/HVDistill
공식 코드https://github.com/zhaoxy92/GLaRA
공식 코드GLaRA: Graph-based Labeling Rule Augmentation for Weakly Supervised Named Entity Recognition
https://github.com/zhenxuan-zhang/gema_score
공식 코드GEMA-Score: Granular Explainable Multi-Agent Score for Radiology Report Evaluation
https://github.com/zhhvvv/cner-uav
공식 코드https://github.com/zhzhengit/LinkNER
공식 코드LinkNER: Linking Local Named Entity Recognition Models to Large Language Models using Uncertainty
https://github.com/zihanwangki/fffner
공식 코드https://github.com/zjunlp/DeepKE/tree/main/example/ner/cross
공식 코드One Model for All Domains: Collaborative Domain-Prefix Tuning for Cross-Domain NER
https://github.com/zjunlp/DeepKE/tree/main/example/ner/few-shot
공식 코드LightNER: A Lightweight Tuning Paradigm for Low-resource NER via Pluggable Prompting
https://github.com/zjunlp/HVPNeT
공식 코드https://github.com/zjunlp/MKGformer
공식 코드Hybrid Transformer with Multi-level Fusion for Multimodal Knowledge Graph Completion
https://github.com/zjunlp/PromptKG/tree/main/research/RetroPrompt
공식 코드Decoupling Knowledge from Memorization: Retrieval-augmented Prompt Learning
https://github.com/zjunlp/deepke
공식 코드DeepKE: A Deep Learning Based Knowledge Extraction Toolkit for Knowledge Base Population
https://github.com/zjunlp/promptkg
공식 코드Decoupling Knowledge from Memorization: Retrieval-augmented Prompt Learning
https://github.com/zl-liu/radiation-oncology-nlp-database
공식 코드https://github.com/zliucr/CrossNER
공식 코드https://github.com/zliucr/coach
공식 코드Coach: A Coarse-to-Fine Approach for Cross-domain Slot Filling
https://github.com/zmd971202/OpenNER
공식 코드Neural Correction Model for Open-Domain Named Entity Recognition
https://github.com/zqtan1024/sequence-to-set
공식 코드A Sequence-to-Set Network for Nested Named Entity Recognition
https://github.com/zslin177/srl-as-gp
공식 코드Fast and Accurate End-to-End Span-based Semantic Role Labeling as Word-based Graph Parsing
https://github.com/zwkatgithub/DSCAU
공식 코드De-biasing Distantly Supervised Named Entity Recognition via Causal Intervention
https://github.com/zwkatgithub/HGL
공식 코드Denoising Distantly Supervised Named Entity Recognition via a Hypergeometric Probabilistic Model
https://github.com/zyz0000/finbert-mrc
공식 코드https://github.com/zzz47zzz/CFNER
공식 코드Distilling Causal Effect from Miscellaneous Other-Class for Continual Named Entity Recognition
https://huggingface.co/facebook/xlm-v-base
공식 코드XLM-V: Overcoming the Vocabulary Bottleneck in Multilingual Masked Language Models
https://worksheets.codalab.org/worksheets/0x2ae89944846444539c2d08a0b7ff3f6f
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.