Results 11 to 20 of about 6,924 (296)
Instance-Based Neural Dependency Parsing
Transactions of the Association for Computational Linguistics, 2021 Interpretable rationales for model predictions are crucial in practical applications. We develop neural models that possess an interpretable inference process for dependency parsing.
Hiroki Ouchi +6 more
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Sorting Out Dependency Parsing [PDF]
, 2008 This paper explores the idea that non-projective dependency parsing can be conceived as the outcome of two interleaved processes, one that sorts the words of a sentence into a canonical order, and one that performs strictly projective dependency parsing on the sorted input.
Joakim Nivre, Nivre, Joakim,
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Event Detection Using a Self-Constructed Dependency and Graph Convolution Network
Applied Sciences, 2023 The extant event detection models, which rely on dependency parsing, have exhibited commendable efficacy. However, for some long sentences with more words, the results of dependency parsing are more complex, because each word corresponds to a directed ...
Li He +4 more
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An improved joint model: POS tagging and dependency parsing [PDF]
Journal of Artificial Intelligence and Data Mining, 2016 Dependency parsing is a way of syntactic parsing and a natural language that automatically analyzes the dependency structure of sentences, and the input for each sentence creates a dependency graph.
A. Pakzad, B. Minaei Bidgoli
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A Dependency Perspective on RST Discourse Parsing and Evaluation [PDF]
Computational Linguistics, 2018 Computational text-level discourse analysis mostly happens within Rhetorical Structure Theory (RST), whose structures have classically been presented as constituency trees, and relies on data from the RST Discourse Treebank (RST-DT); as a result, the RST
Mathieu Morey +2 more
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Scene Graph Parsing as Dependency Parsing [PDF]
Proceedings of the 2018 Conference of the North American Chapter of
the Association for Computational Linguistics: Human Language
Technologies, Volume 1 (Long Papers), 2018 In this paper, we study the problem of parsing structured knowledge graphs from textual descriptions. In particular, we consider the scene graph representation that considers objects together with their attributes and relations: this representation has been proved useful across a variety of vision and language applications.
Yu-Siang Wang +3 more
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, 2011 Dependency parsing has been a prime focus of NLP research of late due to its ability to help parse languages with a free word order. Dependency parsing has been shown to improve NLP systems in certain languages and in many cases is considered the state of the art in the field.
Green, Nathan
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A Graph-based Model for Joint Chinese Word Segmentation and Dependency Parsing
Transactions of the Association for Computational Linguistics, 2020 Chinese word segmentation and dependency parsing are two fundamental tasks for Chinese natural language processing. The dependency parsing is defined at the word-level.
Yan, Hang, Qiu, Xipeng, Huang, Xuanjing
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Aspect-Based Sentiment Analysis Model Fusing Multi-Channel Graph Convolutional Network [PDF]
Jisuanji gongcheng, 2023 Aspect-Based Sentiment Analysis(ABSA)is a fine-grained sentiment analysis task that aims to analyze the sentiment polarity of multiple specific aspects in a given text.
Haiyang YANG, Xingpeng ZHANG
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Generation as dependency parsing [PDF]
Proceedings of the 40th Annual Meeting on Association for Computational Linguistics - ACL '02, 2001 Natural-Language Generation from flat semantics is an NP-complete problem. This makes it necessary to develop algorithms that run with reasonable efficiency in practice despite the high worst-case complexity. We show how to convert TAG generation problems into dependency parsing problems, which is useful because optimizations in recent dependency ...
Alexander Koller, Kristina Striegnitz
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