Graduate Thesis Or Dissertation
Natural Language Understanding: Deep Learning for Abstract Meaning Representation Public Deposited
https://scholar.colorado.edu/concern/graduate_thesis_or_dissertations/fq977v10d
- Abstract
- In the last few years there have been major improvements in the performance of hard nat- ural language processing tasks due to the application of artificial neural network models. These models replace complex hand-engineered systems for extracting and representing the meaning of human language with systems which learn features based on processing examples of language. In this dissertation, I present deep neural networks for semantic role labeling, and then for Abstract Meaning Representation parsing, and a novel Distributed Abstract Meaning Representation, or DAMR. I then describe a model used to create fixed vector representations of sentence meaning from DAMR. Finally, I use natural language inference to test the quality of the meaning content of these fixed vectors.
- Creator
- Date Issued
- 2017
- Academic Affiliation
- Advisor
- Committee Member
- Degree Grantor
- Commencement Year
- Subject
- Last Modified
- 2019-11-14
- Resource Type
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- Language
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Thumbnail | Title | Date Uploaded | Visibility | Actions |
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naturalLanguageUnderstandingDeepLearningForAbstractMeanin.pdf | 2019-11-14 | Public | Download |