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1
Characterizing News Portrayal of Civil Unrest in Hong Kong, 1998–2020 ...
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2
Jibes & Delights: A Dataset of Targeted Insults and Compliments to Tackle Online Abuse​ ...
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3
Bird’s Eye: Probing for Linguistic Graph Structures with a Simple Information-Theoretic Approach ...
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4
Dependency Patterns of Complex Sentences and Semantic Disambiguation for Abstract Meaning Representation Parsing ...
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5
Phrase-Level Action Reinforcement Learning for Neural Dialog Response Generation ...
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6
10D: Phonology, Morphology and Word Segmentation #1 ...
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7
Sample-efficient Linguistic Generalizations through Program Synthesis: Experiments with Phonology Problems ...
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8
PHMOSpell: Phonological and Morphological Knowledge Guided Chinese Spelling Check ...
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9
19th SIGMORPHON Workshop on Computational Research in Phonetics, Phonology, and Morphology - Part 2 ...
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10
18th SIGMORPHON Workshop on Computational Research in Phonetics, Phonology, and Morphology - Part 1 ...
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11
The Match-Extend Serialization Algorithm in Multiprecedence ...
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12
Recognizing Reduplicated Forms: Finite-State Buffered Machines ...
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13
Correcting Chinese Spelling Errors with Phonetic Pre-training ...
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14
PLOME: Pre-training with Misspelled Knowledge for Chinese Spelling Correction ...
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15
Including Signed Languages in Natural Language Processing ...
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16
When is Char Better Than Subword: A Systematic Study of Segmentation Algorithms for Neural Machine Translation ...
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17
The Reading Machine: a Versatile Framework for Studying Incremental Parsing Strategies ...
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18
To POS Tag or Not to POS Tag: The Impact of POS Tags on Morphological Learning in Low-Resource Settings ...
Abstract: Read paper: https://www.aclanthology.org/2021.acl-long.78 Abstract: Part-of-Speech (POS) tags are routinely included as features in many NLP tasks. However, the importance and usefulness of POS tags needs to be examined as NLP expands to low-resource languages because linguists who provide many annotated resources do not place priority on early identification and tagging of POS. This paper describes an empirical study about the effect that POS tags have on two computational morphological tasks with the Transformer architecture. Each task is tested twice on identical data except for the presence/absence of POS tags, using published data in ten high- to low-resource languages or unpublished linguistic field data in five low-resource languages. We find that the presence or absence of POS tags does not have a significant bearing on performance. In joint segmentation and glossing, the largest average difference is an .09 improvement in F1-scores by removing POS tags. In reinflection, the greatest average ...
Keyword: Computational Linguistics; Condensed Matter Physics; Deep Learning; Electromagnetism; FOS Physical sciences; Information and Knowledge Engineering; Morphology; Neural Network; Semantics
URL: https://underline.io/lecture/25958-to-pos-tag-or-not-to-pos-tag-the-impact-of-pos-tags-on-morphological-learning-in-low-resource-settings
https://dx.doi.org/10.48448/04km-3434
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19
An FST morphological analyzer for the Gitksan language ...
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20
Superbizarre Is Not Superb: Derivational Morphology Improves BERT's Interpretation of Complex Words ...
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