Dependency Parsing
322 papers with code • 14 benchmarks • 14 datasets
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
These leaderboards are used to track progress in Dependency Parsing
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Libraries
Use these libraries to find Dependency Parsing models and implementationsDatasets
Penn Treebank
Universal Dependencies
CoNLL
GENIA
KLUE
GUM
Subtasks
Latest papers
Advancing Hungarian Text Processing with HuSpaCy: Efficient and Accurate NLP Pipelines
This paper presents a set of industrial-grade text processing models for Hungarian that achieve near state-of-the-art performance while balancing resource efficiency and accuracy.
GUIDO: A Hybrid Approach to Guideline Discovery & Ordering from Natural Language Texts
Extracting workflow nets from textual descriptions can be used to simplify guidelines or formalize textual descriptions of formal processes like business processes and algorithms.
Hexatagging: Projective Dependency Parsing as Tagging
rycolab/parsing-as-tagging
•
•
We introduce a novel dependency parser, the hexatagger, that constructs dependency trees by tagging the words in a sentence with elements from a finite set of possible tags.
GENTLE: A Genre-Diverse Multilayer Challenge Set for English NLP and Linguistic Evaluation
We evaluate state-of-the-art NLP systems on GENTLE and find severe degradation for at least some genres in their performance on all tasks, which indicates GENTLE's utility as an evaluation dataset for NLP systems.
A Pilot Study on Dialogue-Level Dependency Parsing for Chinese
zzoay/dialogdep
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•
Dialogue-level dependency parsing has received insufficient attention, especially for Chinese.
CQE: A Comprehensive Quantity Extractor
Compared to other information extraction approaches, interestingly only a few works exist that describe methods for a proper extraction and representation of quantities in text.
Analyzing Vietnamese Legal Questions Using Deep Neural Networks with Biaffine Classifiers
anhtunguyen98/NER-biaffine
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•
ICONIP 2021
In this paper, we propose using deep neural networks to extract important information from Vietnamese legal questions, a fundamental task towards building a question answering system in the legal domain.
BRENT: Bidirectional Retrieval Enhanced Norwegian Transformer
ltgoslo/brent
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•
After training, we also separate the language model, which we call the reader, from the retriever components, and show that this can be fine-tuned on a range of downstream tasks.
Extracting Victim Counts from Text
We cast victim count extraction as a question answering (QA) task with a regression or classification objective.
Generic Dependency Modeling for Multi-Party Conversation
shenwzh3/rede
•
•
To model the dependencies between utterances in multi-party conversations, we propose a simple and generic framework based on the dependency parsing results of utterances.
