A Novel Dependency Framework for Enhancing Discourse Data Analysis
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F25%3AC3P9HZX7" target="_blank" >RIV/00216208:11320/25:C3P9HZX7 - isvavai.cz</a>
Result on the web
<a href="http://arxiv.org/abs/2407.12473" target="_blank" >http://arxiv.org/abs/2407.12473</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.48550/arXiv.2407.12473" target="_blank" >10.48550/arXiv.2407.12473</a>
Alternative languages
Result language
angličtina
Original language name
A Novel Dependency Framework for Enhancing Discourse Data Analysis
Original language description
The development of different theories of discourse structure has led to the establishment of discourse corpora based on these theories. However, the existence of discourse corpora established on different theoretical bases creates challenges when it comes to exploring them in a consistent and cohesive way. This study has as its primary focus the conversion of PDTB annotations into dependency structures. It employs refined BERT-based discourse parsers to test the validity of the dependency data derived from the PDTB-style corpora in English, Chinese, and several other languages. By converting both PDTB and RST annotations for the same texts into dependencies, this study also applies ``dependency distance'' metrics to examine the correlation between RST dependencies and PDTB dependencies in English. The results show that the PDTB dependency data is valid and that there is a strong correlation between the two types of dependency distance. This study presents a comprehensive approach for analyzing and evaluating discourse corpora by employing discourse dependencies to achieve unified analysis. By applying dependency representations, we can extract data from PDTB, RST, and SDRT corpora in a coherent and unified manner. Moreover, the cross-linguistic validation establishes the framework's generalizability beyond English. The establishment of this comprehensive dependency framework overcomes limitations of existing discourse corpora, supporting a diverse range of algorithms and facilitating further studies in computational discourse analysis and language sciences.
Czech name
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Czech description
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Classification
Type
J<sub>ost</sub> - Miscellaneous article in a specialist periodical
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
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Others
Publication year
2024
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
ArXiv
ISSN
2331-8422
e-ISSN
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Volume of the periodical
2024
Issue of the periodical within the volume
2024-07-17
Country of publishing house
US - UNITED STATES
Number of pages
29
Pages from-to
1-29
UT code for WoS article
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EID of the result in the Scopus database
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