https://github.com/azminewasi/banglaautokg
공식 코드BanglaAutoKG: Automatic Bangla Knowledge Graph Construction with Semantic Neural Graph Filtering
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/badripatro/mamba360
공식 코드https://github.com/baidu/lac
공식 코드https://github.com/baozuyi/MLMA
공식 코드Low-Resource Sequence Labeling via Unsupervised Multilingual Contextualized Representations
https://github.com/berlino/nest-trans-em18
공식 코드A Neural Transition-based Model for Nested Mention Recognition
https://github.com/beyonderxx/instructuie
공식 코드InstructUIE: Multi-task Instruction Tuning for Unified Information Extraction
https://github.com/beyonderxx/miner
공식 코드https://github.com/beyondguo/genius
공식 코드https://github.com/bflashcp3f/deer
공식 코드Label-Guided In-Context Learning for Named Entity Recognition
https://github.com/bheinzerling/subword-sequence-tagging
공식 코드https://github.com/bids-xu-lab/clinical_entity_recognition_using_gpt_models
공식 코드Improving Large Language Models for Clinical Named Entity Recognition via Prompt Engineering
https://github.com/bionlplab/radtext
공식 코드Radiology Text Analysis System (RadText): Architecture and Evaluation
https://github.com/bionlu-coling2024/biomed-ner-intent_detection
공식 코드Intent Detection and Entity Extraction from BioMedical Literature
https://github.com/bladedancer957/finer
공식 코드https://github.com/blazejdolicki/multilingual-analysis
공식 코드Analysing The Impact Of Linguistic Features On Cross-Lingual Transfer
https://github.com/blcuicall/nlp-crowdsourcing
공식 코드https://github.com/blester125/constrained-decoding
공식 코드Constrained Decoding for Computationally Efficient Named Entity Recognition Taggers
https://github.com/blester125/iobes
공식 코드https://github.com/bloomberg/kbir_keybart
공식 코드https://github.com/bltlab/paranames
공식 코드https://github.com/bltlab/seqscore
공식 코드SeqScore: Addressing Barriers to Reproducible Named Entity Recognition Evaluation
https://github.com/bo1929/anelfop
공식 코드Focusing on Potential Named Entities During Active Label Acquisition
https://github.com/boleima/topro
공식 코드ToPro: Token-Level Prompt Decomposition for Cross-Lingual Sequence Labeling Tasks
https://github.com/bonaventuredossou/mlm_al
공식 코드AfroLM: A Self-Active Learning-based Multilingual Pretrained Language Model for 23 African Languages
https://github.com/bonaventuredossou/multitask_fon
공식 코드https://github.com/boschresearch/adversarial_meta_embeddings
공식 코드FAME: Feature-Based Adversarial Meta-Embeddings for Robust Input Representations
https://github.com/boschresearch/sofc-exp_textmining_resources
공식 코드The SOFC-Exp Corpus and Neural Approaches to Information Extraction in the Materials Science Domain
https://github.com/bowang-lab/joint-ner-and-re
공식 코드End-to-end Named Entity Recognition and Relation Extraction using Pre-trained Language Models
https://github.com/bplank/DaNplus
공식 코드DaN+: Danish Nested Named Entities and Lexical Normalization
https://github.com/bplank/danish_ner_transfer
공식 코드Neural Cross-Lingual Transfer and Limited Annotated Data for Named Entity Recognition in Danish
https://github.com/br-ai-ns-institute/zero-shotner
공식 코드https://github.com/brentbiseda/w266_project
공식 코드Enhancing Pharmacovigilance with Drug Reviews and Social Media
https://github.com/btaille/contener
공식 코드Contextualized Embeddings in Named-Entity Recognition: An Empirical Study on Generalization
https://github.com/btaille/sincere
공식 코드Let's Stop Incorrect Comparisons in End-to-end Relation Extraction!
https://github.com/c3sr/split-ner
공식 코드Split-NER: Named Entity Recognition via Two Question-Answering-based Classifications
https://github.com/caisa-lab/llms-real-world-noise-robustness
공식 코드Exploring Robustness of Multilingual LLMs on Real-World Noisy Data
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.