MOLOR | Morphologically Linked Old Irish Resource

Summary
The aim of MOLOR—Morphologically Linked Old Irish Resource—is to make Old Irish distributed lexical resources interact by using state-of-the-art data models and lexicographic standards based on the Linguistic Linked Open Data (LLOD) principles. On the basis of the 8th-century Old Irish Würzburg glosses, MOLOR will fully exploit a set of existing (both textual and lexical) resources by linking the text with a full-form lexicon containing both normalised and variant spellings as well as phonological representations. The integration of resources will benefit many different stakeholders, including lexicographers, philologists, and students, who currently work with inadequate and fragmented resources for a language with a highly complex morphology and an inconsistent and opaque orthography.

Thanks to the internationally recognised expertise of the host institution, the applicant will be at the forefront of developments in LLOD and language processing for ancient languages. As a result of the envisaged mutual knowledge transfer, MOLOR is not only expected to lead to a novel standard in resource creation and interlinking for Old Irish, but it will also substantially contribute to and improve language-independent lexicographic data formats and ontologies, as such being applicable to any language and any domain. Finally, the fellowship will significantly improve the applicant’s skillset and employability due to increased interdisciplinary expertise at the intersection of the Humanities and Technology, and the fostering of new partnerships on resource creation and streamlining for ancient Indo-European languages.
Unfold all
/
Fold all
More information & hyperlinks
Web resources: https://cordis.europa.eu/project/id/101106220
Start date: 01-10-2023
End date: 30-09-2025
Total budget - Public funding: - 172 750,00 Euro
Cordis data

Original description

The aim of MOLOR—Morphologically Linked Old Irish Resource—is to make Old Irish distributed lexical resources interact by using state-of-the-art data models and lexicographic standards based on the Linguistic Linked Open Data (LLOD) principles. On the basis of the 8th-century Old Irish Würzburg glosses, MOLOR will fully exploit a set of existing (both textual and lexical) resources by linking the text with a full-form lexicon containing both normalised and variant spellings as well as phonological representations. The integration of resources will benefit many different stakeholders, including lexicographers, philologists, and students, who currently work with inadequate and fragmented resources for a language with a highly complex morphology and an inconsistent and opaque orthography.

Thanks to the internationally recognised expertise of the host institution, the applicant will be at the forefront of developments in LLOD and language processing for ancient languages. As a result of the envisaged mutual knowledge transfer, MOLOR is not only expected to lead to a novel standard in resource creation and interlinking for Old Irish, but it will also substantially contribute to and improve language-independent lexicographic data formats and ontologies, as such being applicable to any language and any domain. Finally, the fellowship will significantly improve the applicant’s skillset and employability due to increased interdisciplinary expertise at the intersection of the Humanities and Technology, and the fostering of new partnerships on resource creation and streamlining for ancient Indo-European languages.

Status

SIGNED

Call topic

HORIZON-MSCA-2022-PF-01-01

Update Date

31-07-2023
Images
No images available.
Geographical location(s)
Structured mapping
Unfold all
/
Fold all
Horizon Europe
HORIZON.1 Excellent Science
HORIZON.1.2 Marie Skłodowska-Curie Actions (MSCA)
HORIZON.1.2.0 Cross-cutting call topics
HORIZON-MSCA-2022-PF-01
HORIZON-MSCA-2022-PF-01-01 MSCA Postdoctoral Fellowships 2022