@techreport{Bigeardetal2023,
title = {Interlingual Index for the Easier project's core sign languages},
author = {Sam Bigeard and Marc Schulder and Maria Kopf and Thomas Hanke and Kiriaki Vasilaki and Anna Vacalopoulou and Theodoros Goulas and Dimou Athanasia–Lida and Stavroula-Evita Fotinea and Eleni Efthimiou and Neil Fox and Onno Crasborn and Lianne Westenberg and Sarah Ebling and Laure Wawrinka},
url = {https://www.fdr.uni-hamburg.de/record/12676},
doi = {10.25592/UHHFDM.12675},
year = {2023},
date = {2023-06-30},
urldate = {2023-06-30},
abstract = {The purpose of the inter-lingual index is to link the lexical resources from the different languages of the project and make them machine-readable. The earlier deliverable D6.3 was the first<br> version of this index. It included German Sign Language (DGS) and Greek Sign Language<br> (GSL). This deliverable is the second version of the index. It covers further core sign languages of the project: British Sign Language (BSL), Sign Language of the Netherlands (NGT), French Sign Language (LSF) and Swiss-German Sign Language (DSGS). The next version will be deliverable 6.5 and will include languages beyond the project’s core languages. The deliverable is the index itself. This report provides background information on wordnet<br> research, explains our method and choices, and presents the resulting dataset. Our interlingual index uses the wordnet concept of synonym sets (synsets), which define concepts by gathering signs and words that can represent the same meaning. This approach is more resistant to translation mistakes stemming from translation pairs being only valid for certain word/sign meanings. It also provides a new way to define sign types that does not rely on<br> approximate translations to a single spoken language word, the way glosses do. As a basis for our index, we build on the synset inventory of Open Multilingual Wordnet (OMW). We use a three-step method: The first step is automatically matching candidate synsets to signs using the keywords and glosses associated with the sign. The second step is automatically<br> validating links that are most likely to be correct. The final step is manual validation of the<br> remaining links, prioritising the most useful signs. This work has resulted in a dataset of 7929 signs in 6 sign languages linked to 11806 synsets. Additionally, a web interface has been launched to make the index accessible for the general public.},
keywords = {},
pubstate = {published},
tppubtype = {techreport}
}
