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NER
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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/neukg/techgpt-2.0
공식 코드TechGPT-2.0: A large language model project to solve the task of knowledge graph construction
https://github.com/neulab/InterpretEval
공식 코드Interpretable Multi-dataset Evaluation for Named Entity Recognition
https://github.com/neulab/spanner
공식 코드https://github.com/neuralmind-ai/portuguese-bert
공식 코드https://github.com/nguyennth/joint-ib-models
공식 코드Span-based Named Entity Recognition by Generating and Compressing Information
https://github.com/nguyenvulebinh/vietnamese-roberta
공식 코드https://github.com/niclasgriesshaber/gemini_historical_dataset_pipeline
공식 코드Multimodal LLMs for OCR, OCR Post-Correction, and Named Entity Recognition in Historical Documents
https://github.com/niclasgriesshaber/llm_historical_dataset_benchmarking
공식 코드Multimodal LLMs for OCR, OCR Post-Correction, and Named Entity Recognition in Historical Documents
https://github.com/nicolamelluso/SkillNER
공식 코드https://github.com/nicpopovic/ember
공식 코드https://github.com/nicpopovic/stoke
공식 코드https://github.com/nimameghdadi/uottawa-at-legallens-2024-transformer-based-classification
공식 코드uOttawa at LegalLens-2024: Transformer-based Classification Experiments
https://github.com/ningkko/umls_colloquial
공식 코드Streamlining Social Media Information Retrieval for COVID-19 Research with Deep Learning
https://github.com/ningkko/umls_colloquialism
공식 코드Streamlining Social Media Information Retrieval for COVID-19 Research with Deep Learning
https://github.com/nlpwm-whu/tadner
공식 코드Type-Aware Decomposed Framework for Few-Shot Named Entity Recognition
https://github.com/npoe/covid-qa
공식 코드https://github.com/ntunlp/Zero-Shot-Cross-Lingual-NER
공식 코드https://github.com/ntunlp/kmlm
공식 코드Enhancing Multilingual Language Model with Massive Multilingual Knowledge Triples
https://github.com/ntunlp/multisense_embedding_alignment
공식 코드Towards Multi-Sense Cross-Lingual Alignment of Contextual Embeddings
https://github.com/onurgu/joint-ner-and-md-tagger
공식 코드Improving Named Entity Recognition by Jointly Learning to Disambiguate Morphological Tags
https://github.com/opennlg/openba-v2
공식 코드OpenBA-V2: Reaching 77.3% High Compression Ratio with Fast Multi-Stage Pruning
https://github.com/osu-nlp-group/bio-tokenization
공식 코드Biomedical Language Models are Robust to Sub-optimal Tokenization
https://github.com/ottowg/gsap-ner
공식 코드https://github.com/pablorom2004/insight-buddy-ai-app
공식 코드https://github.com/paramansh/propaganda_detection
공식 코드https://github.com/pavanbaswani/fincausal_sharedtask-2023
공식 코드https://github.com/pefimov/cross-lingual-adjustment
공식 코드The Impact of Cross-Lingual Adjustment of Contextual Word Representations on Zero-Shot Transfer
https://github.com/pfliu-nlp/Named-Entity-Recognition-NER-Papers
공식 코드Rethinking Generalization of Neural Models: A Named Entity Recognition Case Study
https://github.com/phenixace/MFE-NER
공식 코드MFE-NER: Multi-feature Fusion Embedding for Chinese Named Entity Recognition
https://github.com/pkunlp-icler/censor
공식 코드https://github.com/pkunlp-icler/scl-rai
공식 코드https://github.com/pluslabnlp/clap
공식 코드Contextual Label Projection for Cross-Lingual Structured Prediction
https://github.com/qingyu-qc/bioner_gerbera
공식 코드Augmenting Biomedical Named Entity Recognition with General-domain Resources
https://github.com/qiuhaolu/tner
공식 코드Large Language Models Struggle in Token-Level Clinical Named Entity Recognition
https://github.com/qznan/spankl
공식 코드A Neural Span-Based Continual Named Entity Recognition Model
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