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Universal Dependencies 2.9
Zeman, Daniel; Nivre, Joakim; Abrams, Mitchell. - : Universal Dependencies Consortium, 2021
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2
Universal Dependencies 2.8.1
Zeman, Daniel; Nivre, Joakim; Abrams, Mitchell. - : Universal Dependencies Consortium, 2021
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3
Universal Dependencies 2.8
Zeman, Daniel; Nivre, Joakim; Abrams, Mitchell. - : Universal Dependencies Consortium, 2021
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4
Universal Dependencies 2.7
Zeman, Daniel; Nivre, Joakim; Abrams, Mitchell. - : Universal Dependencies Consortium, 2020
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5
Universal Dependencies 2.6
Zeman, Daniel; Nivre, Joakim; Abrams, Mitchell. - : Universal Dependencies Consortium, 2020
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6
Learning Contextualised Cross-lingual Word Embeddings and Alignments for Extremely Low-Resource Languages Using Parallel Corpora ...
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7
Development of a computer-assisted Japanese functional expression learning system for Chinese-speaking learners [<Journal>]
Liu, Jun [Verfasser]; Shindo, Hiroyuki [Verfasser]; Matsumoto, Yuji [Verfasser]
DNB Subject Category Language
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8
Universal Dependencies 2.5
Zeman, Daniel; Nivre, Joakim; Abrams, Mitchell. - : Universal Dependencies Consortium, 2019
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9
Universal Dependencies 2.4
Nivre, Joakim; Abrams, Mitchell; Agić, Željko. - : Universal Dependencies Consortium, 2019
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10
Universal Dependencies 2.2
In: https://hal.archives-ouvertes.fr/hal-01930733 ; 2018 (2018)
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11
Universal Dependencies 2.3
Nivre, Joakim; Abrams, Mitchell; Agić, Željko. - : Universal Dependencies Consortium, 2018
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12
Universal Dependencies 2.2
Nivre, Joakim; Abrams, Mitchell; Agić, Željko. - : Universal Dependencies Consortium, 2018
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13
Universal Dependencies 2.1
In: https://hal.inria.fr/hal-01682188 ; 2017 (2017)
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14
Universal Dependencies 2.0 alpha (obsolete)
Nivre, Joakim; Agić, Željko; Ahrenberg, Lars. - : Universal Dependencies Consortium, 2017
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15
CoNLL 2017 Shared Task System Outputs
Zeman, Daniel; Potthast, Martin; Straka, Milan. - : Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL), 2017
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16
Universal Dependencies 2.0
Nivre, Joakim; Agić, Željko; Ahrenberg, Lars. - : Universal Dependencies Consortium, 2017
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17
Universal Dependencies 2.0 – CoNLL 2017 Shared Task Development and Test Data
Nivre, Joakim; Agić, Željko; Ahrenberg, Lars. - : Universal Dependencies Consortium, 2017
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18
Universal Dependencies 2.1
Nivre, Joakim; Agić, Željko; Ahrenberg, Lars. - : Universal Dependencies Consortium, 2017
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19
MWE-Aware English Dependency Corpus
Kato, Akihiko; Shindo, Hiroyuki; Matsumoto, Yuji. - : Linguistic Data Consortium, 2017. : https://www.ldc.upenn.edu, 2017
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20
MWE-Aware English Dependency Corpus 2.0
Kato, Akihiko; Shindo, Hiroyuki; Matsumoto, Yuji. - : Linguistic Data Consortium, 2017. : https://www.ldc.upenn.edu, 2017
Abstract: *Introduction* MWE-Aware English Dependency Corpus Version 2.0 was developed by the Nara Institute of Science and Technology Computational Linguistics Laboratory and consists of English compound function words annotated in dependency format. The data is derived from OntoNotes Release 5.0 (LDC2013T19). Compound functions words are a type of multiword expression (MWE). MWEs are groups of tokens that can be treated as a single semantic or syntactic unit. Doing so facilitates natural language processing tasks such as constituency and dependency parsing. Version 2.0 adds annotations of named entities (persons, locations, organizations) into dependency trees that are aware of compound function words. Version 1.0 is available from LDC as MWE-Aware English Dependency Corpus (LDC2017T01). *Data* MWE-Aware English Dependency Corpus Version 2.0 was derived from the Wall Street Journal portion of OntoNotes Release 5.0. MWEs were identified in OntoNotes' phrase structure trees and each MWE was established as a single subtree. Those phrase structure subtrees were then converted to a dependency structure (the Stanford dependencies) in CoNLL format. The data is split into 1,728 phrase structure trees as *.parse files and a single 14-column tab separated dependency as a *.conll file. Both file types are encoded as UTF-8. *Samples* Please view this sample. *Updates* None at this time.
URL: https://catalog.ldc.upenn.edu/LDC2017T16
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