https://github.com/personads/ud-selection
공식 코드Genre as Weak Supervision for Cross-lingual Dependency Parsing
Papers with Code 아카이브
Dependency Parsing
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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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/pkunlp-icler/atp
공식 코드ATP: AMRize Then Parse! Enhancing AMR Parsing with PseudoAMRs
https://github.com/pmulcaire/rosita
공식 코드Polyglot Contextual Representations Improve Crosslingual Transfer
https://github.com/ppfliu/open-intent-discovery
공식 코드Open Intent Discovery through Unsupervised Semantic Clustering and Dependency Parsing
https://github.com/qipeng/arc-swift
공식 코드https://github.com/rasoolims/ImageTranslate
공식 코드"Wikily" Supervised Neural Translation Tailored to Cross-Lingual Tasks
https://github.com/rdgcn/rdgcn
공식 코드RDGCN: Reinforced Dependency Graph Convolutional Network for Aspect-based Sentiment Analysis
https://github.com/rotmanguy/DCST
공식 코드Deep Contextualized Self-training for Low Resource Dependency Parsing
https://github.com/rtmdrr/replicability-analysis-NLP
공식 코드Replicability Analysis for Natural Language Processing: Testing Significance with Multiple Datasets
https://github.com/ruisi-su/concrete_dep
공식 코드https://github.com/rycolab/pareto-probing
공식 코드https://github.com/rycolab/parsing-as-tagging
공식 코드https://github.com/rycolab/spanningtrees
공식 코드Please Mind the Root: Decoding Arborescences for Dependency Parsing
https://github.com/rycolab/wpda
공식 코드https://github.com/sarves/thamizhi-pos
공식 코드https://github.com/sarves/thamizhi-udp
공식 코드https://github.com/satya77/cqe_evaluation
공식 코드https://github.com/sauravcsvt/KDD_linelisting
공식 코드Guided Deep List: Automating the Generation of Epidemiological Line Lists from Open Sources
https://github.com/sebastian-nehrdich/byt5-sanskrit-analyzers
공식 코드One Model is All You Need: ByT5-Sanskrit, a Unified Model for Sanskrit NLP Tasks
https://github.com/selgroup/masgcn
공식 코드https://github.com/shenwzh3/rede
공식 코드https://github.com/shijie-wu/crosslingual-nlp
공식 코드Beto, Bentz, Becas: The Surprising Cross-Lingual Effectiveness of BERT
https://github.com/shiquanyang/GraphDialog
공식 코드GraphDialog: Integrating Graph Knowledge into End-to-End Task-Oriented Dialogue Systems
https://github.com/shuheikurita/semrl
공식 코드Multi-Task Semantic Dependency Parsing with Policy Gradient for Learning Easy-First Strategies
https://github.com/slanglab/transition_sampler
공식 코드Monte Carlo Syntax Marginals for Exploring and Using Dependency Parses
https://github.com/social-machines/tweebanknlp
공식 코드https://github.com/sonvx/word2vecVN
공식 코드https://github.com/spyflying/LSCM-Refseg
공식 코드Linguistic Structure Guided Context Modeling for Referring Image Segmentation
https://github.com/stanfordnlp/stanfordnlp
공식 코드https://github.com/stanfordnlp/stanza
공식 코드Stanza: A Python Natural Language Processing Toolkit for Many Human Languages
https://github.com/statsmaths/cleanNLP
공식 코드A Tidy Data Model for Natural Language Processing using cleanNLP
https://github.com/strubell/LISA
공식 코드Linguistically-Informed Self-Attention for Semantic Role Labeling
https://github.com/sustcsonglin/second-order-neural-dmv
공식 코드https://github.com/sustcsonglin/span-based-dependency-parsing
공식 코드https://github.com/tarotis/building-an-endangered-language-resource-in-the-classroom
공식 코드Building an Endangered Language Resource in the Classroom: Universal Dependencies for Kakataibo
https://github.com/tchewik/e2e-microtexts
공식 코드End-to-End Argument Mining over Varying Rhetorical Structures
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.