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공식 코드Tackling Error Propagation through Reinforcement Learning: A Case of Greedy 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).
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
Tackling Error Propagation through Reinforcement Learning: A Case of Greedy Dependency Parsing
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Is POS Tagging Necessary or Even Helpful for Neural Dependency Parsing?
Cross-lingual Parsing with Polyglot Training and Multi-treebank Learning: A Faroese Case Study
Controlling Hallucinations at Word Level in Data-to-Text Generation
Rethinking Self-Attention: Towards Interpretability in Neural Parsing
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Building a Kannada POS Tagger Using Machine Learning and Neural Network Models
Growing Trees on Sounds: Assessing Strategies for End-to-End Dependency Parsing of Speech
Does syntax matter? A strong baseline for Aspect-based Sentiment Analysis with RoBERTa
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.