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From neural discourse parsing to content structuring : towards a large-scale data-driven approach to discourse processing Guz, Grigorii Anatolievich
Abstract
In this thesis, we propose novel approaches for supervised RST-style discourse parsing, as well as the methods for utilizing those discourse structures for the benefit of natural language generation. We demonstrate a significant improvement in discourse parsing accuracy on RST-DT and Instr-DT treebanks by incorporating silver-standard supervision. Furthermore, in line with theoretical and empirical connections between the discourse parsing and coreference resolution tasks, we find the evidence of improvement of discourse parsing accuracy on RST-DT when our proposed discourse parsing system is provided with coreference supervision from a coreference resolver trained on OntoNotes corpus. Finally, in extending our work to natural language generation, we demonstrate that our novel content structuring system utilizing silver-standard discourse structures outperforms text-only systems on our proposed task of elementary discourse unit ordering, a significantly more difficult version of sentence ordering task.
Item Metadata
| Title |
From neural discourse parsing to content structuring : towards a large-scale data-driven approach to discourse processing
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| Creator | |
| Supervisor | |
| Publisher |
University of British Columbia
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| Date Issued |
2021
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| Description |
In this thesis, we propose novel approaches for supervised RST-style discourse parsing, as well as the methods for utilizing those discourse structures for the benefit of natural language generation. We demonstrate a significant improvement in discourse parsing accuracy on RST-DT and Instr-DT treebanks by incorporating silver-standard supervision. Furthermore, in line with theoretical and empirical connections between the discourse parsing and coreference resolution tasks, we find the evidence of improvement of discourse parsing accuracy on RST-DT when our proposed discourse parsing system is provided with coreference supervision from a coreference resolver trained on OntoNotes corpus. Finally, in extending our work to natural language generation, we demonstrate that our novel content structuring system utilizing silver-standard discourse structures outperforms text-only systems on our proposed task of elementary discourse unit ordering, a significantly more difficult version of sentence ordering task.
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| Genre | |
| Type | |
| Language |
eng
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| Date Available |
2021-05-04
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| Provider |
Vancouver : University of British Columbia Library
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| Rights |
Attribution-NonCommercial-NoDerivatives 4.0 International
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| DOI |
10.14288/1.0397220
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| URI | |
| Degree | |
| Program | |
| Affiliation | |
| Degree Grantor |
University of British Columbia
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| Graduation Date |
2021-11
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| Campus | |
| Scholarly Level |
Graduate
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| Rights URI | |
| Aggregated Source Repository |
DSpace
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Rights
Attribution-NonCommercial-NoDerivatives 4.0 International