AI2D-RST: a multimodal corpus of 1000 primary school science diagrams.
This article introduces AI2D-RST, a multimodal corpus of 1000 English-language diagrams that represent topics in primary school natural sciences, such as food webs, life cycles, moon phases and human physiology. The corpus is based on the Allen Institute for Artificial Intelligence Diagrams (AI2D) d...
| Publicado en: | Language Resources & Evaluation Vol. 55; no. 3; pp. 661 - 689 |
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| Autores principales: | , , , , , , , , |
| Formato: | Artículo |
| Publicado: |
Springer Nature
Sep2021
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| Materias: | |
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=151686296&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 151686296 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 1574020X 179V jtl: Language Resources & Evaluation issn: 1574020X maglogo: N pubinfo: dt: Sep2021 vid: 55 iid: 3 pid: 237 pub: Springer Nature artinfo: ui: 151686296 10.1007/s10579-020-09517-1 ppf: 661 ppct: 28 formats: fmt: – @attributes: type: T – @attributes: type: P size: 2.1MB tig: atl: AI2D-RST: a multimodal corpus of 1000 primary school science diagrams. aug: au: Hiippala, Tuomo Alikhani, Malihe Haverinen, Jonas Kalliokoski, Timo Logacheva, Evanfiya Orekhova, Serafina Tuomainen, Aino Stone, Matthew Bateman, John A. affil: Department of Languages, University of Helsinki, P.O. Box 24, 00014, Helsinki, Finland School of Computing and Information, University of Pittsburgh, Pittsburgh, USA Department of Computer Science, Rutgers University, New Brunswick, USA Faculty 10: Linguistics and Literary Studies, Bremen University, Bremen, Germany su: Primary schools Lunar phases Corpora Structural analysis (Engineering) Human physiology sug: subj: Primary schools Lunar phases Corpora Structural analysis (Engineering) Human physiology keyword: Diagrams Graphs Multimodality Rhetorical Structure Theory ab: This article introduces AI2D-RST, a multimodal corpus of 1000 English-language diagrams that represent topics in primary school natural sciences, such as food webs, life cycles, moon phases and human physiology. The corpus is based on the Allen Institute for Artificial Intelligence Diagrams (AI2D) dataset, a collection of diagrams with crowdsourced descriptions, which was originally developed to support research on automatic diagram understanding and visual question answering. Building on the segmentation of diagram layouts in AI2D, the AI2D-RST corpus presents a new multi-layer annotation schema that provides a rich description of their multimodal structure. Annotated by trained experts, the layers describe (1) the grouping of diagram elements into perceptual units, (2) the connections set up by diagrammatic elements such as arrows and lines, and (3) the discourse relations between diagram elements, which are described using Rhetorical Structure Theory (RST). Each annotation layer in AI2D-RST is represented using a graph. The corpus is freely available for research and teaching. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y custom: Language Resources & Evaluation is a copyright of Springer, 2021. All Rights Reserved. item: Language Resources & Evaluation holder: Springer Nature dt: @attributes: year: 2021 holdings: @attributes: islocal: N |
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