Dependency Parsing Edit Task
Natural Language Processing
About
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).
Benchmarks
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Libraries
Subtasks
Datasets
Greatest papers with code
Semi-Supervised Sequence Modeling with Cross-View Training
EMNLP 2018
• tensorflow/models
• 
We therefore propose Cross-View Training (CVT), a semi-supervised learning algorithm that improves the representations of a Bi-LSTM sentence encoder using a mix of labeled and unlabeled data.
Ranked #1 on
CCG Supertagging
on CCGBank
CCG SUPERTAGGING DEPENDENCY PARSING MACHINE TRANSLATION MULTI-TASK LEARNING NAMED ENTITY RECOGNITION PART-OF-SPEECH TAGGING UNSUPERVISED REPRESENTATION LEARNING
DRAGNN: A Transition-based Framework for Dynamically Connected Neural Networks
In this work, we present a compact, modular framework for constructing novel recurrent neural architectures.
Globally Normalized Transition-Based Neural Networks
ACL 2016
• tensorflow/models
•
Our model is a simple feed-forward neural network that operates on a task-specific transition system, yet achieves comparable or better accuracies than recurrent models.
Ranked #15 on
Dependency Parsing
on Penn Treebank
DEPENDENCY PARSING PART-OF-SPEECH TAGGING SENTENCE COMPRESSION
CamemBERT: a Tasty French Language Model
ACL 2020
• huggingface/transformers
• 
We show that the use of web crawled data is preferable to the use of Wikipedia data.
Ranked #1 on
Dependency Parsing
on Spoken Corpus
DEPENDENCY PARSING LANGUAGE MODELLING NAMED ENTITY RECOGNITION NATURAL LANGUAGE INFERENCE PART-OF-SPEECH TAGGING
Stanza: A Python Natural Language Processing Toolkit for Many Human Languages
ACL 2020
• stanfordnlp/stanza
•
We introduce Stanza, an open-source Python natural language processing toolkit supporting 66 human languages.
COREFERENCE RESOLUTION DEPENDENCY PARSING LEMMATIZATION NAMED ENTITY RECOGNITION RELATION EXTRACTION TOKENIZATION
N-LTP: A Open-source Neural Chinese Language Technology Platform with Pretrained Models
• HIT-SCIR/ltp
•
We introduce N-LTP, an open-source Python Chinese natural language processing toolkit supporting five basic tasks: Chinese word segmentation, part-of-speech tagging, named entity recognition, dependency parsing, and semantic dependency parsing.
CHINESE WORD SEGMENTATION DEPENDENCY PARSING KNOWLEDGE DISTILLATION NAMED ENTITY RECOGNITION PART-OF-SPEECH TAGGING SEMANTIC DEPENDENCY PARSING
Deep Biaffine Attention for Neural Dependency Parsing
• dmlc/gluon-nlp
• 
This paper builds off recent work from Kiperwasser & Goldberg (2016) using neural attention in a simple graph-based dependency parser.
Ranked #2 on
Dependency Parsing
on CoNLL-2009
DisSent: Sentence Representation Learning from Explicit Discourse Relations
• facebookresearch/InferSent
•
Learning effective representations of sentences is one of the core missions of natural language understanding.
DEPENDENCY PARSING NATURAL LANGUAGE UNDERSTANDING SENTENCE EMBEDDINGS
Towards Better UD Parsing: Deep Contextualized Word Embeddings, Ensemble, and Treebank Concatenation
CONLL 2018
• HIT-SCIR/ELMoForManyLangs
•
This paper describes our system (HIT-SCIR) submitted to the CoNLL 2018 shared task on Multilingual Parsing from Raw Text to Universal Dependencies.
Ranked #3 on
Dependency Parsing
on Universal Dependencies