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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
Formalization of AMR Inference via Hybrid Logic Tableaux ...
Goldner, Eli Tecumseh. - : Brandeis University, 2022
Abstract: AMR and its extensions have become popular in semantic representation due to their ease of annotation by non-experts, attention to the predicative core of sentences, and abstraction away from syntactic matter. An area where AMR and its extensions warrant improvement is formalization and suitability for inference, where it is lacking compared to other semantic representations, such as description logics, episodic logic, and discourse representation theory. This thesis presents a formalization of inference over a merging of Donatelli et al.’s (2018) AMR extension for tense and aspect with Pustejovsky et al.’s (2019) AMR extension for quantification and scope. Inference is modeled with a merging of Hansen’s (2007) tableau method for first-order hybrid logic with varying domain semantics (FHL) and Blackburn and Jørgensen’s (2012) tableau method for basic hybrid tense logic (BHTL). We motivate the merging of these AMR variants, present their interpretation and inference in the combination of FHL and BHTL, which ...
Keyword: Abstract Meaning Representation; AMR; automated reasoning; Computational Linguistics; hybrid logic; Knowledge Representation; semantic representation; Semantics; tableau
URL: https://dx.doi.org/10.48617/etd.45
https://scholarworks.brandeis.edu/esploro/outputs/graduate/9924022111401921
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5
Chinese character decomposition for neural MT with multi-word expressions
In: Han, Lifeng orcid:0000-0002-3221-2185 , Jones, Gareth J.F. orcid:0000-0003-2923-8365 , Smeaton, Alan F. orcid:0000-0003-1028-8389 and Bolzoni, Paolo (2021) Chinese character decomposition for neural MT with multi-word expressions. In: 23rd Nordic Conference on Computational Linguistics (NoDaLiDa 2021), 31 May- 2 June 2021, Reykjavik, Iceland (Online). (In Press) (2021)
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6
Dependency Patterns of Complex Sentences and Semantic Disambiguation for Abstract Meaning Representation Parsing ...
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7
Phrase-Level Action Reinforcement Learning for Neural Dialog Response Generation ...
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8
10D: Phonology, Morphology and Word Segmentation #1 ...
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9
Sample-efficient Linguistic Generalizations through Program Synthesis: Experiments with Phonology Problems ...
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10
19th SIGMORPHON Workshop on Computational Research in Phonetics, Phonology, and Morphology - Part 2 ...
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11
18th SIGMORPHON Workshop on Computational Research in Phonetics, Phonology, and Morphology - Part 1 ...
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12
SpeakEasy Pronunciation Trainer: Personalized Multimodal Pronunciation Training ...
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13
The Match-Extend Serialization Algorithm in Multiprecedence ...
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14
Recognizing Reduplicated Forms: Finite-State Buffered Machines ...
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15
Correcting Chinese Spelling Errors with Phonetic Pre-training ...
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16
PLOME: Pre-training with Misspelled Knowledge for Chinese Spelling Correction ...
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17
SpeakEasy Pronunciation Trainer: Personalized Multimodal Pronunciation Training ...
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18
Including Signed Languages in Natural Language Processing ...
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19
Quantification: the view from natural language generation ...
Carstensen, Kai-Uwe. - : Universitätsbibliothek Siegen, 2021
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20
When is Char Better Than Subword: A Systematic Study of Segmentation Algorithms for Neural Machine Translation ...
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