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).

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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.

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

13 Mar 2017tensorflow/models

In this work, we present a compact, modular framework for constructing novel recurrent neural architectures.

DEPENDENCY PARSING MULTI-TASK LEARNING

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.

DEPENDENCY PARSING PART-OF-SPEECH TAGGING SENTENCE COMPRESSION

N-LTP: A Open-source Neural Chinese Language Technology Platform with Pretrained Models

24 Sep 2020HIT-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

6 Nov 2016dmlc/gluon-nlp

This paper builds off recent work from Kiperwasser & Goldberg (2016) using neural attention in a simple graph-based dependency parser.

DEPENDENCY PARSING

DisSent: Sentence Representation Learning from Explicit Discourse Relations

12 Oct 2017facebookresearch/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.

DEPENDENCY PARSING WORD EMBEDDINGS