@inproceedings{otto-etal-2024-corpus,
title = "A Corpus of {G}erman {A}bstract {M}eaning {R}epresentation ({D}e{AMR})",
author = "Otto, Christoph and
Groschwitz, Jonas and
Koller, Alexander and
Yang, Xiulin and
Donatelli, Lucia",
editor = "Calzolari, Nicoletta and
Kan, Min-Yen and
Hoste, Veronique and
Lenci, Alessandro and
Sakti, Sakriani and
Xue, Nianwen",
booktitle = "Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)",
month = may,
year = "2024",
address = "Torino, Italia",
publisher = "ELRA and ICCL",
url = "https://aclanthology.org/2024.lrec-main.26/",
pages = "286--292",
abstract = "We present the first comprehensive set of guidelines for German Abstract Meaning Representation (Deutsche AMR, DeAMR) along with an annotated corpus of 400 DeAMR. Taking English AMR (EnAMR) as our starting point, we propose significant adaptations to faithfully represent the structure and semantics of German, focusing particularly on verb frames, compound words, and modality. We validate our annotation through inter-annotator agreement and further evaluate our corpus with a comparison of structural divergences between EnAMR and DeAMR on parallel sentences, replicating previous work that finds both cases of cross-lingual structural alignment and cases of meaningful linguistic divergence. Finally, we fine-tune state-of-the-art multi-lingual and cross-lingual AMR parsers on our corpus and find that, while our small corpus is insufficient to produce quality output, there is a need to continue develop and evaluate against gold non-English AMR data."
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%0 Conference Proceedings
%T A Corpus of German Abstract Meaning Representation (DeAMR)
%A Otto, Christoph
%A Groschwitz, Jonas
%A Koller, Alexander
%A Yang, Xiulin
%A Donatelli, Lucia
%Y Calzolari, Nicoletta
%Y Kan, Min-Yen
%Y Hoste, Veronique
%Y Lenci, Alessandro
%Y Sakti, Sakriani
%Y Xue, Nianwen
%S Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)
%D 2024
%8 May
%I ELRA and ICCL
%C Torino, Italia
%F otto-etal-2024-corpus
%X We present the first comprehensive set of guidelines for German Abstract Meaning Representation (Deutsche AMR, DeAMR) along with an annotated corpus of 400 DeAMR. Taking English AMR (EnAMR) as our starting point, we propose significant adaptations to faithfully represent the structure and semantics of German, focusing particularly on verb frames, compound words, and modality. We validate our annotation through inter-annotator agreement and further evaluate our corpus with a comparison of structural divergences between EnAMR and DeAMR on parallel sentences, replicating previous work that finds both cases of cross-lingual structural alignment and cases of meaningful linguistic divergence. Finally, we fine-tune state-of-the-art multi-lingual and cross-lingual AMR parsers on our corpus and find that, while our small corpus is insufficient to produce quality output, there is a need to continue develop and evaluate against gold non-English AMR data.
%U https://aclanthology.org/2024.lrec-main.26/
%P 286-292
Markdown (Informal)
[A Corpus of German Abstract Meaning Representation (DeAMR)](https://aclanthology.org/2024.lrec-main.26/) (Otto et al., LREC-COLING 2024)
ACL
- Christoph Otto, Jonas Groschwitz, Alexander Koller, Xiulin Yang, and Lucia Donatelli. 2024. A Corpus of German Abstract Meaning Representation (DeAMR). In Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024), pages 286–292, Torino, Italia. ELRA and ICCL.