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Part-Of-Speech Tagging
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Part-of-speech tagging (POS tagging) is the task of tagging a word in a text with its part of speech. A part of speech is a category of words with similar grammatical properties. Common English parts of speech are noun, verb, adjective, adverb, pronoun, preposition, conjunction, etc.
Example:
| Vinken | , | 61 | years | old |
|---|---|---|---|---|
| NNP | , | CD | NNS | JJ |
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/bheinzerling/subword-sequence-tagging
공식 코드https://github.com/bjerva/semantic-tagging
공식 코드https://github.com/boknilev/nmt-repr-analysis
공식 코드https://github.com/boleima/topro
공식 코드ToPro: Token-Level Prompt Decomposition for Cross-Lingual Sequence Labeling Tasks
https://github.com/bonaventuredossou/multitask_fon
공식 코드https://github.com/boschresearch/steps-parser
공식 코드https://github.com/bplank/bilstm-aux
공식 코드https://github.com/bplank/semi-supervised-baselines
공식 코드Strong Baselines for Neural Semi-supervised Learning under Domain Shift
https://github.com/bplank/wnut-2017-pos-norm
공식 코드To Normalize, or Not to Normalize: The Impact of Normalization on Part-of-Speech Tagging
https://github.com/cambridgeltl/parameter-factorization
공식 코드Parameter Space Factorization for Zero-Shot Learning across Tasks and Languages
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/chiang9/NLP-Chinese_couplet_generation
공식 코드https://github.com/cic4k/wisebe
공식 코드https://github.com/cindyxinyiwang/emea
공식 코드Efficient Test Time Adapter Ensembling for Low-resource Language Varieties
https://github.com/cominsys/FRAKE
공식 코드https://github.com/conglei2xu/global-context-mechanism
공식 코드Supplementary Features of BiLSTM for Enhanced Sequence Labeling
https://github.com/danifg/DiscoPointer
공식 코드https://github.com/datquocnguyen/BioNLP
공식 코드From POS tagging to dependency parsing for biomedical event extraction
https://github.com/datquocnguyen/BioPosDep
공식 코드From POS tagging to dependency parsing for biomedical event extraction
https://github.com/datquocnguyen/VnMarMoT
공식 코드https://github.com/datquocnguyen/jPTDP
공식 코드A Novel Neural Network Model for Joint POS Tagging and Graph-based Dependency Parsing
https://github.com/dbamman/latin-bert
공식 코드Latin BERT: A Contextual Language Model for Classical Philology
https://github.com/deadcardassian/poscorefimpact
공식 코드https://github.com/disk0Dancer/rubert-finetuned-pos
공식 코드POS-tagging to highlight the skeletal structure of sentences
https://github.com/divamgupta/mtl_girnet
공식 코드GIRNet: Interleaved Multi-Task Recurrent State Sequence Models
https://github.com/drbenchmark/drbenchmark
공식 코드DrBenchmark: A Large Language Understanding Evaluation Benchmark for French Biomedical Domain
https://github.com/dsfsi/puoberta
공식 코드PuoBERTa: Training and evaluation of a curated language model for Setswana
https://github.com/dsfsi/puodata
공식 코드PuoBERTa: Training and evaluation of a curated language model for Setswana
https://github.com/edoost/pert
공식 코드Persian Ezafe Recognition Using Transformers and Its Role in Part-Of-Speech Tagging
https://github.com/emorynlp/bert-2019
공식 코드https://github.com/emorynlp/elit
공식 코드https://github.com/emorynlp/seq2seq-corenlp
공식 코드https://github.com/ethch18/specializing-multilingual
공식 코드Specializing Multilingual Language Models: An Empirical Study
https://github.com/facebookresearch/llama-hd-dataset
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.