https://github.com/cambridgeltl/parameter-factorization
공식 코드Parameter Space Factorization for Zero-Shot Learning across Tasks and Languages
Papers with Code 아카이브
Named Entity Recognition (NER)
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- 평가표
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- 439
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/cambridgeltl/xcopa
공식 코드MAD-X: An Adapter-Based Framework for Multi-Task Cross-Lingual Transfer
https://github.com/cardiffnlp/tweetnlp
공식 코드TweetNLP: Cutting-Edge Natural Language Processing for Social Media
https://github.com/casparswift/da_mim
공식 코드A Simple Information-Based Approach to Unsupervised Domain-Adaptive Aspect-Based Sentiment Analysis
https://github.com/cathyshyr/rare_disease_phenotype_extraction
공식 코드Identifying and Extracting Rare Disease Phenotypes with Large Language Models
https://github.com/cbluebenchmark/cblue
공식 코드CBLUE: A Chinese Biomedical Language Understanding Evaluation Benchmark
https://github.com/ccied/ugforum-analysis
공식 코드Identifying Products in Online Cybercrime Marketplaces: A Dataset for Fine-grained Domain Adaptation
https://github.com/cdli-gh/Semi-Supervised-NMT-for-Sumerian-English
공식 코드How Low is Too Low? A Computational Perspective on Extremely Low-Resource Languages
https://github.com/cdli-gh/Sumerian-Translation-Pipeline
공식 코드How Low is Too Low? A Computational Perspective on Extremely Low-Resource Languages
https://github.com/cfiltnlp/hiner
공식 코드https://github.com/cgraywang/deepstruct
공식 코드DeepStruct: Pretraining of Language Models for Structure Prediction
https://github.com/chancefocus/pixiu
공식 코드PIXIU: A Large Language Model, Instruction Data and Evaluation Benchmark for Finance
https://github.com/changdejie/diaKG-code
공식 코드DiaKG: an Annotated Diabetes Dataset for Medical Knowledge Graph Construction
https://github.com/chanzuckerberg/MedMentions
공식 코드MedMentions: A Large Biomedical Corpus Annotated with UMLS Concepts
https://github.com/chen700564/metaner-icl
공식 코드https://github.com/chen700564/sdnet
공식 코드Few-shot Named Entity Recognition with Self-describing Networks
https://github.com/chen700564/supercd
공식 코드Few-shot Named Entity Recognition via Superposition Concept Discrimination
https://github.com/chongzhangfdu/tpp
공식 코드Reading Order Matters: Information Extraction from Visually-rich Documents by Token Path Prediction
https://github.com/christos42/CLDR_CLNER_models
공식 코드Imposing Relation Structure in Language-Model Embeddings Using Contrastive Learning
https://github.com/christos42/inductive_bias_IE
공식 코드An Information Extraction Study: Take In Mind the Tokenization!
https://github.com/cimm-kzn/RuDReC
공식 코드https://github.com/cindyxinyiwang/emea
공식 코드Efficient Test Time Adapter Ensembling for Low-resource Language Varieties
https://github.com/ckgconstruction/bdcp
공식 코드Robust Few-Shot Named Entity Recognition with Boundary Discrimination and Correlation Purification
https://github.com/clab/stack-lstm-ner
공식 코드https://github.com/clairebarale/refugee_cases_ner
공식 코드Automated Refugee Case Analysis: An NLP Pipeline for Supporting Legal Practitioners
https://github.com/cliang1453/BOND
공식 코드BOND: BERT-Assisted Open-Domain Named Entity Recognition with Distant Supervision
https://github.com/cocacola-lab/chatie
공식 코드ChatIE: Zero-Shot Information Extraction via Chatting with ChatGPT
https://github.com/cocacola-lab/collabkg
공식 코드https://github.com/cod3licious/conec
공식 코드Context encoders as a simple but powerful extension of word2vec
https://github.com/codermusou/nflat4cner
공식 코드NFLAT: Non-Flat-Lattice Transformer for Chinese Named Entity Recognition
https://github.com/cogstack/foresight
공식 코드Foresight -- Generative Pretrained Transformer (GPT) for Modelling of Patient Timelines using EHRs
https://github.com/compnet/ddaugner
공식 코드Data Augmentation for Robust Character Detection in Fantasy Novels
https://github.com/compnet/splice
공식 코드The Role of Natural Language Processing Tasks in Automatic Literary Character Network Construction
https://github.com/conglei2xu/global-context-mechanism
공식 코드Supplementary Features of BiLSTM for Enhanced Sequence Labeling
https://github.com/contextscout/gcn_ner
공식 코드https://github.com/cosylabiiit/recipe-knowledge-mining
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.