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1
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
Well-Defined Morphology is Sentence-Level Morphology ...
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5
Applying the Transformer to Character-level Transduction
In: Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume (2021)
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6
Telling BERT's Full Story: from Local Attention to Global Aggregation
In: Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume (2021)
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7
Disambiguatory Signals are Stronger in Word-initial Positions
In: Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume (2021)
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8
Minimal Supervision for Morphological Inflection ...
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9
Asking It All: Generating Contextualized Questions for any Semantic Role ...
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10
The Possible, the Plausible, and the Desirable: Event-Based Modality Detection for Language Processing ...
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11
Formae reformandae: for a reorganisation of verb form annotation in Universal Dependencies illustrated by the specific case of Latin
Cecchini, Flavio Massimiliano (orcid:0000-0001-9029-1822). - : Association for Computational Linguistics, 2021. : country:BGR, 2021. : place:Sofia, 2021
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12
RelWalk - A Latent Variable Model Approach to Knowledge Graph Embedding.
Bollegala, Danushka; Kawarabayashi, Ken-ichi; Yoshida, Yuichi. - : Association for Computational Linguistics, 2021
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13
Dictionary-based Debiasing of Pre-trained Word Embeddings.
Bollegala, Danushka; Kaneko, Masahiro. - : Association for Computational Linguistics, 2021
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14
Debiasing Pre-trained Contextualised Embeddings.
Kaneko, Masahiro; Bollegala, Danushka. - : Association for Computational Linguistics, 2021
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15
Is supervised syntactic parsing beneficial for language understanding tasks? An empirical investigation
Glavaš, Goran; Vulić, Ivan. - : Association for Computational Linguistics, 2021
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16
Universal Dependencies 2.7
Zeman, Daniel; Nivre, Joakim; Abrams, Mitchell. - : Universal Dependencies Consortium, 2020
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17
Universal Dependencies 2.6
Zeman, Daniel; Nivre, Joakim; Abrams, Mitchell. - : Universal Dependencies Consortium, 2020
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18
Universal Dependencies 2.5
Zeman, Daniel; Nivre, Joakim; Abrams, Mitchell. - : Universal Dependencies Consortium, 2019
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19
Universal Dependencies 2.4
Nivre, Joakim; Abrams, Mitchell; Agić, Željko. - : Universal Dependencies Consortium, 2019
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20
Joint Transition-Based Models for Morpho-Syntactic Parsing: Parsing Strategies for MRLs and a Case Study from Modern Hebrew
In: Transactions of the Association for Computational Linguistics, Vol 7, Pp 33-48 (2019) (2019)
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