Dependency Parsing
322 papers with code • 15 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).
Libraries
Use these libraries to find Dependency Parsing models and implementationsDatasets
Subtasks
Most implemented papers
Seq2seq Dependency Parsing
This paper presents a sequence to sequence (seq2seq) dependency parser by directly predicting the relative position of head for each given word, which therefore results in a truly end-to-end seq2seq dependency parser for the first time.
LINSPECTOR: Multilingual Probing Tasks for Word Representations
We present a reusable methodology for creation and evaluation of such tests in a multilingual setting.
75 Languages, 1 Model: Parsing Universal Dependencies Universally
We present UDify, a multilingual multi-task model capable of accurately predicting universal part-of-speech, morphological features, lemmas, and dependency trees simultaneously for all 124 Universal Dependencies treebanks across 75 languages.
Generalizing Natural Language Analysis through Span-relation Representations
Natural language processing covers a wide variety of tasks predicting syntax, semantics, and information content, and usually each type of output is generated with specially designed architectures.
Parsing as Pretraining
We first cast constituent and dependency parsing as sequence tagging.
KLUE: Korean Language Understanding Evaluation
We introduce Korean Language Understanding Evaluation (KLUE) benchmark.
Yara Parser: A Fast and Accurate Dependency Parser
At its fastest, Yara can parse about 4000 sentences per second when in greedy mode (1 beam).
Neural End-to-End Learning for Computational Argumentation Mining
Contrary to models that operate on the argument component level, we find that framing AM as dependency parsing leads to subpar performance results.
VnCoreNLP: A Vietnamese Natural Language Processing Toolkit
We present an easy-to-use and fast toolkit, namely VnCoreNLP---a Java NLP annotation pipeline for Vietnamese.
Scene Graph Parsing as Dependency Parsing
The scene graphs generated by our learned neural dependency parser achieve an F-score similarity of 49. 67% to ground truth graphs on our evaluation set, surpassing best previous approaches by 5%.