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Discourse cohesion in Xenophon’s On Horsemanship through Sketch Engine

Abstract:
We build a Sketch Engine corpus for Xenophon’s classical Greek scientific treatise On Horsemanship. Sketch Engine is a web-based corpus-analysis tool that allows the user to inspect the lexical makeup of a text (cf. keyword lists), explore the surroundings of select items (cf. concordances) and identify fixed expressions in a text (cf. n-grams). We make available our corpus-preparation tool and our corpus configuration file for Sketch Engine. We use the Sketch Engine corpus to detect discontinuous verbal multi-word expressions, specifically support-verb constructions (e.g. to take a decision). We examine how support-verb constructions – through their structural and lexical properties – aid discourse coherence and cohesion throughout Xenophon’s treatise. We furthermore examine how the recurring support-verb constructions in the treatise reflect the scientific register of the text. The article shows how an understudied category of lexico-syntactic device (support-verb constructions) in classical Greek majorly aids discourse cohesion, structurally and contextually speaking. It also shows how an understudied text in the form of a technical treatise (On Horsemanship) majorly furthers insight into scientific literacy of the classical period. Finally, by making available our corpus-preparation tool and code, we hope to further collaboration and adaptation and thus improvement of existing tools and counteract the multiplication of tools.
Publication status:
Published
Peer review status:
Peer reviewed

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Publication website:
https://dhq.digitalhumanities.org/vol/17/3/000683/000683.html

Authors


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Institution:
University of Oxford
Division:
HUMS
Department:
Classics
Oxford college:
Christ Church
Role:
Author
ORCID:
0000-0001-6302-3726
More by this author
Role:
Author
ORCID:
0000-0003-0336-4419


Publisher:
Association for Computers and the Humanities
Journal:
Digital Humanities Quarterly More from this journal
Volume:
17
Issue:
3
Publication date:
2023-01-01
Acceptance date:
2023-01-01
EISSN:
1938-4122


Language:
English
Pubs id:
1557812
Local pid:
pubs:1557812
Deposit date:
2024-10-26

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