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1
Syntactic Nuclei in Dependency Parsing -- A Multilingual Exploration ...
Basirat, Ali; Nivre, Joakim. - : arXiv, 2021
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2
Attention Can Reflect Syntactic Structure (If You Let It) ...
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3
Schrödinger's Tree -- On Syntax and Neural Language Models ...
Kulmizev, Artur; Nivre, Joakim. - : arXiv, 2021
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4
Køpsala: Transition-Based Graph Parsing via Efficient Training and Effective Encoding ...
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5
Understanding Pure Character-Based Neural Machine Translation: The Case of Translating Finnish into English ...
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6
Universal Dependencies v2: An Evergrowing Multilingual Treebank Collection ...
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7
Do Neural Language Models Show Preferences for Syntactic Formalisms? ...
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8
Deep Contextualized Word Embeddings in Transition-Based and Graph-Based Dependency Parsing -- A Tale of Two Parsers Revisited ...
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9
Encoders Help You Disambiguate Word Senses in Neural Machine Translation ...
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10
82 Treebanks, 34 Models: Universal Dependency Parsing with Multi-Treebank Models ...
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11
An Analysis of Attention Mechanisms: The Case of Word Sense Disambiguation in Neural Machine Translation ...
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12
Dependency Parsing of Turkish ...
Eryigit, Gulsen; Nivre, Joakim; Oflazer, Kemal. - : Carnegie Mellon University, 2008
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13
Dependency Parsing of Turkish ...
Eryigit, Gulsen; Nivre, Joakim; Oflazer, Kemal. - : Carnegie Mellon University, 2008
Abstract: The suitability of different parsing methods for different languages is an important topic in syntactic parsing. Especially lesser-studied languages, typologically different from the languages for which methods have originally been developed, pose interesting challenges in this respect. This article presents an investigation of data-driven dependency parsing of Turkish, an agglutinative, free constituent order language that can be seen as the representative of a wider class of languages of similar type. Our investigations show that morphological structure plays an essential role in finding syntactic relations in such a language. In particular, we show that employing sublexical units called inflectional groups , rather than word forms, as the basic parsing units improves parsing accuracy. We test our claim on two different parsing methods, one based on a probabilistic model with beam search and the other based on discriminative classifiers and a deterministic parsing strategy, and show that the usefulness of ...
Keyword: 200402 Computational Linguistics; 80107 Natural Language Processing; Applied Computer Science; FOS Computer and information sciences; FOS Languages and literature
URL: https://dx.doi.org/10.1184/r1/6287600.v1
https://kilthub.cmu.edu/articles/Dependency_Parsing_of_Turkish/6287600/1
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