Mod-D2T: A Multi-layer Dataset for Modular Data-to-Text Generation
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F23%3AK35LBLCV" target="_blank" >RIV/00216208:11320/23:K35LBLCV - isvavai.cz</a>
Result on the web
<a href="https://aclanthology.org/2023.inlg-main.36/" target="_blank" >https://aclanthology.org/2023.inlg-main.36/</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.18653/v1/2023.inlg-main.36" target="_blank" >10.18653/v1/2023.inlg-main.36</a>
Alternative languages
Result language
angličtina
Original language name
Mod-D2T: A Multi-layer Dataset for Modular Data-to-Text Generation
Original language description
"Rule-based text generators lack the coverage and fluency of their neural counterparts, but have two big advantages over them: (i) they are entirely controllable and do not hallucinate; and (ii) they can fully explain how an output was generated from an input. In this paper we leverage these two advantages to create large and reliable synthetic datasets with multiple human-intelligible intermediate representations. We present the Modular Data-to-Text (Mod-D2T) Dataset which incorporates ten intermediate-level representations between input triple sets and output text; the mappings from one level to the next can broadly be interpreted as the traditional modular tasks of an NLG pipeline. We describe the Mod-D2T dataset, evaluate its quality via manual validation and discuss its applications and limitations. Data, code and documentation are available at https://github.com/mille-s/Mod-D2T."
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
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
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
"Proceedings of the 16th International Natural Language Generation Conference"
ISBN
979-8-89176-001-1
ISSN
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e-ISSN
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Number of pages
12
Pages from-to
455-466
Publisher name
""
Place of publication
Prague, Czechia
Event location
Prague, Czechia
Event date
Jan 1, 2023
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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