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NER

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평가표: 6
보존된 평가 기록: 4

The named entity recognition (NER) involves identification of key information in the text and classification into a set of predefined categories. This includes standard entities in the text like Part of Speech (PoS) and entities like places, names etc...

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/asahi417/tner

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T-NER: An All-Round Python Library for Transformer-based Named Entity Recognition

https://github.com/asappresearch/spoken-ner

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On the Use of External Data for Spoken Named Entity Recognition

https://github.com/astrazeneca/kazu

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Biomedical NER for the Enterprise with Distillated BERN2 and the Kazu Framework

https://github.com/aub-mind/araBERT

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AraBERT: Transformer-based Model for Arabic Language Understanding

https://github.com/ayoubhammal/ckss4ner

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Few-Shot Domain Adaptation for Named-Entity Recognition via Joint Constrained k-Means and Subspace Selection

https://github.com/azminewasi/banglaautokg

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BanglaAutoKG: Automatic Bangla Knowledge Graph Construction with Semantic Neural Graph Filtering

https://github.com/badripatro/mamba360

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Mamba-360: Survey of State Space Models as Transformer Alternative for Long Sequence Modelling: Methods, Applications, and Challenges

https://github.com/baozuyi/MLMA

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Low-Resource Sequence Labeling via Unsupervised Multilingual Contextualized Representations

https://github.com/beyonderxx/miner

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MINER: Improving Out-of-Vocabulary Named Entity Recognition from an Information Theoretic Perspective

https://github.com/beyondguo/genius

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GENIUS: Sketch-based Language Model Pre-training via Extreme and Selective Masking for Text Generation and Augmentation

https://github.com/bflashcp3f/deer

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Label-Guided In-Context Learning for Named Entity Recognition

https://github.com/bids-xu-lab/clinical_entity_recognition_using_gpt_models

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Improving Large Language Models for Clinical Named Entity Recognition via Prompt Engineering

https://github.com/bionlu-coling2024/biomed-ner-intent_detection

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Intent Detection and Entity Extraction from BioMedical Literature

https://github.com/bladedancer957/finer

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Federated Incremental Named Entity Recognition

https://github.com/blazejdolicki/multilingual-analysis

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Analysing The Impact Of Linguistic Features On Cross-Lingual Transfer

https://github.com/blcuicall/nlp-crowdsourcing

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Cost-efficient Crowdsourcing for Span-based Sequence Labeling: Worker Selection and Data Augmentation

https://github.com/blester125/constrained-decoding

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Constrained Decoding for Computationally Efficient Named Entity Recognition Taggers

https://github.com/bloomberg/kbir_keybart

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Learning Rich Representation of Keyphrases from Text

https://github.com/bltlab/seqscore

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SeqScore: Addressing Barriers to Reproducible Named Entity Recognition Evaluation

https://github.com/bo1929/anelfop

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Focusing on Potential Named Entities During Active Label Acquisition

https://github.com/boleima/topro

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ToPro: Token-Level Prompt Decomposition for Cross-Lingual Sequence Labeling Tasks

https://github.com/bonaventuredossou/mlm_al

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AfroLM: A Self-Active Learning-based Multilingual Pretrained Language Model for 23 African Languages

https://github.com/bonaventuredossou/multitask_fon

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FonMTL: Towards Multitask Learning for the Fon Language

https://github.com/boschresearch/adversarial_meta_embeddings

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FAME: Feature-Based Adversarial Meta-Embeddings for Robust Input Representations

https://github.com/bowang-lab/joint-ner-and-re

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End-to-end Named Entity Recognition and Relation Extraction using Pre-trained Language Models

https://github.com/bplank/DaNplus

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DaN+: Danish Nested Named Entities and Lexical Normalization

https://github.com/bplank/danish_ner_transfer

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Neural Cross-Lingual Transfer and Limited Annotated Data for Named Entity Recognition in Danish

https://github.com/br-ai-ns-institute/zero-shotner

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From Zero to Hero: Harnessing Transformers for Biomedical Named Entity Recognition in Zero- and Few-shot Contexts

https://github.com/btaille/sincere

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Let's Stop Incorrect Comparisons in End-to-end Relation Extraction!

https://github.com/c3sr/split-ner

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Split-NER: Named Entity Recognition via Two Question-Answering-based Classifications

https://github.com/caisa-lab/llms-real-world-noise-robustness

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Exploring Robustness of Multilingual LLMs on Real-World Noisy Data

https://github.com/cambridgeltl/parameter-factorization

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Parameter Space Factorization for Zero-Shot Learning across Tasks and Languages

https://github.com/casparswift/da_mim

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A Simple Information-Based Approach to Unsupervised Domain-Adaptive Aspect-Based Sentiment Analysis

https://github.com/cathyshyr/rare_disease_phenotype_extraction

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Identifying and Extracting Rare Disease Phenotypes with Large Language Models

https://github.com/cfiltnlp/hiner

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HiNER: A Large Hindi Named Entity Recognition Dataset

https://github.com/chen700564/metaner-icl

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Learning In-context Learning for Named Entity Recognition

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