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Living Machines atypical animacy dataset

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LwM-nlp-animacy-annotations-machines19thC.zip

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Resource type
Dataset
Creator (Person)
Tolfo, Giorgia
Ahnert, Ruth
ORCIDORCID logo
Beelen, Kaspar
ORCIDORCID logo
Coll Ardanuy, Mariona
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Lawrence, Jon
ORCIDORCID logo
McDonough, Katherine
ORCIDORCID logo
Nanni, Federico
ORCIDORCID logo
Wilson, Daniel C.S.
ORCIDORCID logo
Date published
October 30, 2020
Abstract
Atypical animacy detection dataset, based on nineteenth-century sentences in English extracted from an open dataset of nineteenth-century books digitized by the British Library (available via https://doi.org/10.21250/db14, British Library Labs, 2014). This dataset contains 598 sentences containing mentions of machines. Each sentence has been annotated according to the animacy and humanness of the machine in the sentence. This dataset has been created as part of the following paper: Ardanuy, M. C., F. Nanni, K. Beelen, Kasra Hosseini, Ruth Ahnert, J. Lawrence, Katherine McDonough, Giorgia Tolfo, D. C. Wilson and B. McGillivray. "Living Machines: A study of atypical animacy." In Proceedings of the 28th International Conference on Computational Linguistics (COLING2020).
Contributor (organisation)
British Library
Living with Machines
Project(s)
Living with Machines
Funder
Funder nameAwards
Engineering and Physical Sciences Research Council
EP/N510129/1
Alan Turing Institute
EP/N510129/1
Arts and Humanities Research Council
AH/S01179X/1
Publisher
British Library
Place of publication
London, UK
Official URL
https://doi.org/10.23636/1215
Related URL
https://doi.org/10.21250/db14
Licence
https://creativecommons.org/publicdomain/zero/1.0/
DOI
10.23636/1215
Keywords
digital history
natural language processing
digital humanities
atypical animacy
Living with Machines
computational linguistics
Additional information
This dataset was produced as part of Living with Machines. This project, funded by the UK Research and Innovation (UKRI) Strategic Priority Fund, is a multidisciplinary collaboration delivered by the Arts and Humanities Research Council (AHRC grant AH/S01179X/1), with The Alan Turing Institute, the British Library and the Universities of Cambridge, East Anglia, Exeter, and Queen Mary University of London. This work was also supported by The Alan Turing Institute (EPSRC grant EP/ N510129/1).
Collection
Living with Machines
Managed by the British Library and supported by the AHRC

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