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        <title>Multilingual Abstract Meaning Representation for Celtic Languages</title>
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            <title>Proceedings of the 4th Celtic Language Technology Workshop within LREC2022</title>
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            <namePart type="given">Theodorus</namePart>
            <namePart type="family">Fransen</namePart>
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    <abstract>Deep Semantic Parsing into Abstract Meaning Representation (AMR) graphs has reached a high quality with neural-based seq2seq approaches. However, the training corpus for AMR is only available for English. Several approaches to process other languages exist, but only for high resource languages. We present an approach to create a multilingual text-to-AMR model for three Celtic languages, Welsh (P-Celtic) and the closely related Irish and Scottish-Gaelic (Q-Celtic). The main success of this approach are underlying multilingual transformers like mT5. We finally show that machine translated test corpora unfairly improve the AMR evaluation for about 1 or 2 points (depending on the language).</abstract>
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%0 Conference Proceedings
%T Multilingual Abstract Meaning Representation for Celtic Languages
%A Heinecke, Johannes
%A Shimorina, Anastasia
%Y Fransen, Theodorus
%Y Lamb, William
%Y Prys, Delyth
%S Proceedings of the 4th Celtic Language Technology Workshop within LREC2022
%D 2022
%8 June
%I European Language Resources Association
%C Marseille, France
%F heinecke-shimorina-2022-multilingual
%X Deep Semantic Parsing into Abstract Meaning Representation (AMR) graphs has reached a high quality with neural-based seq2seq approaches. However, the training corpus for AMR is only available for English. Several approaches to process other languages exist, but only for high resource languages. We present an approach to create a multilingual text-to-AMR model for three Celtic languages, Welsh (P-Celtic) and the closely related Irish and Scottish-Gaelic (Q-Celtic). The main success of this approach are underlying multilingual transformers like mT5. We finally show that machine translated test corpora unfairly improve the AMR evaluation for about 1 or 2 points (depending on the language).
%U https://aclanthology.org/2022.cltw-1.1
%P 1-6

Markdown (Informal)

[Multilingual Abstract Meaning Representation for Celtic Languages](https://aclanthology.org/2022.cltw-1.1) (Heinecke & Shimorina, CLTW 2022)

• Multilingual Abstract Meaning Representation for Celtic Languages (Heinecke & Shimorina, CLTW 2022)

ACL

• Johannes Heinecke and Anastasia Shimorina. 2022. Multilingual Abstract Meaning Representation for Celtic Languages. In Proceedings of the 4th Celtic Language Technology Workshop within LREC2022, pages 1–6, Marseille, France. European Language Resources Association.