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1
Neural Token Segmentation for High Token-Internal Complexity ...
Brusilovsky, Idan; Tsarfaty, Reut. - : arXiv, 2022
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2
Morphological Reinflection with Multiple Arguments: An Extended Annotation schema and a Georgian Case Study ...
Abstract: In recent years, a flurry of morphological datasets had emerged, most notably UniMorph, a multi-lingual repository of inflection tables. However, the flat structure of the current morphological annotation schema makes the treatment of some languages quirky, if not impossible, specifically in cases of polypersonal agreement, where verbs agree with multiple arguments using true affixes. In this paper, we propose to address this phenomenon by expanding the UniMorph annotation schema to a hierarchical feature structure that naturally accommodates complex argument marking. We apply this extended schema to one such language, Georgian, and provide a human-verified, accurate and balanced morphological dataset for Georgian verbs. The dataset has 4 times more tables and 6 times more verb forms compared to the existing UniMorph dataset, covering all possible variants of argument marking, demonstrating the adequacy of our proposed scheme. Experiments with a standard reinflection model show that generalization is easy ... : ACL 2022 ...
Keyword: Computation and Language cs.CL; FOS Computer and information sciences
URL: https://arxiv.org/abs/2203.08527
https://dx.doi.org/10.48550/arxiv.2203.08527
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3
Exploiting emojis for abusive language detection
Wiegand, Michael [Verfasser]; Ruppenhofer, Josef [Verfasser]; Merlo, Paola [Herausgeber]. - Mannheim : Leibniz-Institut für Deutsche Sprache (IDS), Bibliothek, 2021
DNB Subject Category Language
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4
Implicitly abusive comparisons – a new dataset and linguistic analysis
Wiegand, Michael [Verfasser]; Geulig, Maja [Verfasser]; Ruppenhofer, Josef [Verfasser]. - Mannheim : Leibniz-Institut für Deutsche Sprache (IDS), Bibliothek, 2021
DNB Subject Category Language
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5
Universal Dependencies 2.9
Zeman, Daniel; Nivre, Joakim; Abrams, Mitchell. - : Universal Dependencies Consortium, 2021
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6
Universal Dependencies 2.8.1
Zeman, Daniel; Nivre, Joakim; Abrams, Mitchell. - : Universal Dependencies Consortium, 2021
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7
Universal Dependencies 2.8
Zeman, Daniel; Nivre, Joakim; Abrams, Mitchell. - : Universal Dependencies Consortium, 2021
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8
Minimal Supervision for Morphological Inflection ...
Goldman, Omer; Tsarfaty, Reut. - : arXiv, 2021
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9
Well-Defined Morphology is Sentence-Level Morphology ...
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10
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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11
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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12
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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13
Minimal Supervision for Morphological Inflection ...
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14
Asking It All: Generating Contextualized Questions for any Semantic Role ...
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15
The Possible, the Plausible, and the Desirable: Event-Based Modality Detection for Language Processing ...
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16
The Possible, the Plausible, and the Desirable: Event-Based Modality Detection for Language Processing ...
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17
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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18
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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19
Dictionary-based Debiasing of Pre-trained Word Embeddings.
Bollegala, Danushka; Kaneko, Masahiro. - : Association for Computational Linguistics, 2021
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20
Debiasing Pre-trained Contextualised Embeddings.
Kaneko, Masahiro; Bollegala, Danushka. - : Association for Computational Linguistics, 2021
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