Dependency Parsing
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Dependency parsing is the task of extracting a dependency parse of a sentence that represents its grammatical structure and defines the relationships between "head" words and words, which modify those heads.
Example:
root
|
| +-------dobj---------+
| | |
nsubj | | +------det-----+ | +-----nmod------+
+--+ | | | | | | |
| | | | | +-nmod-+| | | +-case-+ |
+ | + | + + || + | + | |
I prefer the morning flight through Denver
Relations among the words are illustrated above the sentence with directed, labeled arcs from heads to dependents (+ indicates the dependent).
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/ShannonAI/glyce
공식 코드https://github.com/ShannonAI/mrc-for-dependency-parsing
공식 코드https://github.com/Sreyan88/SemEval-2021-Toxic-Spans-Detection
공식 코드https://github.com/TalSchuster/CrossLingualELMo
공식 코드https://github.com/TomokiMatsuno/PACLIC32
공식 코드https://github.com/UKPLab/acl2017-neural_end2end_AM
공식 코드Neural End-to-End Learning for Computational Argumentation Mining
https://github.com/UKPLab/linspector
공식 코드LINSPECTOR: Multilingual Probing Tasks for Word Representations
https://github.com/UKPLab/linspector-web
공식 코드LINSPECTOR WEB: A Multilingual Probing Suite for Word Representations
https://github.com/UniversalDependencies/UD_Bhojpuri-BHTB
공식 코드https://github.com/VinAIResearch/PhoBERT
공식 코드https://github.com/VinAIResearch/PhoNLP
공식 코드https://github.com/WangYuxuan93/CLBT
공식 코드Cross-Lingual BERT Transformation for Zero-Shot Dependency Parsing
https://github.com/WinnieHAN/structure_adv
공식 코드Adversarial Attack and Defense of Structured Prediction Models
https://github.com/XingxingZhang/dense_parser
공식 코드https://github.com/XingxingZhang/td-treelstm
공식 코드https://github.com/XuezheMax/NeuroNLP2
공식 코드https://github.com/YerevaNN/JointUD
공식 코드Towards JointUD: Part-of-speech Tagging and Lemmatization using Recurrent Neural Networks
https://github.com/Yusics/bist-parser
공식 코드https://github.com/adhigunasurya/distillation_parser
공식 코드Distilling an Ensemble of Greedy Dependency Parsers into One MST Parser
https://github.com/adp01/Code-Mixed-Dataset
공식 코드https://github.com/aghie/parsing-as-pretraining
공식 코드https://github.com/ahmetustun/udapter
공식 코드UDapter: Language Adaptation for Truly Universal Dependency Parsing
https://github.com/ai-ku/wvec
공식 코드Substitute Based SCODE Word Embeddings in Supervised NLP Tasks
https://github.com/ajfisch/TypologyParser
공식 코드Working Hard or Hardly Working: Challenges of Integrating Typology into Neural Dependency Parsers
https://github.com/alierkan/Turkish-ABSA
공식 코드https://github.com/alirezamshi/G2GTr
공식 코드Graph-to-Graph Transformer for Transition-based Dependency Parsing
https://github.com/allenai/scibert
공식 코드https://github.com/amikael/ncdigraphs
공식 코드Generic Axiomatization of Families of Noncrossing Graphs in Dependency Parsing
https://github.com/amunozo/multilingual-assessment
공식 코드Assessment of Pre-Trained Models Across Languages and Grammars
https://github.com/anaezquerro/incpar
공식 코드On the Challenges of Fully Incremental Neural Dependency Parsing
https://github.com/anaezquerro/semeval24-task3
공식 코드https://github.com/anaezquerro/separ
공식 코드Hierarchical Bracketing Encodings for Dependency Parsing as Tagging
https://github.com/annaproxy/udify-metalearning
공식 코드Meta-Learning for Fast Cross-Lingual Adaptation in Dependency Parsing
https://github.com/ashishgupta2598/sacti
공식 코드A Novel Multi-Task Learning Approach for Context-Sensitive Compound Type Identification in Sanskrit
https://github.com/asofiaoliveira/srl_bert_pt
공식 코드Improving Portuguese Semantic Role Labeling with Transformers and Transfer Learning
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.