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.
Original language | English |
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Title of host publication | Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024) |
Editors | Nicoletta Calzolari, Min-Yen Kan, Veronique Hoste, Alessandro Lenci, Sakriani Sakti, Nianwen Xue |
Publisher | ELRA and ICCL |
Pages | 286-292 |
Number of pages | 7 |
ISBN (Electronic) | 9782493814104 |
Publication status | Published - 2024 |
Event | Joint 30th International Conference on Computational Linguistics and 14th International Conference on Language Resources and Evaluation, LREC-COLING 2024 - Hybrid, Torino, Italy Duration: 20 May 2024 → 25 May 2024 |
Conference
Conference | Joint 30th International Conference on Computational Linguistics and 14th International Conference on Language Resources and Evaluation, LREC-COLING 2024 |
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Country/Territory | Italy |
City | Hybrid, Torino |
Period | 20/05/24 → 25/05/24 |
Bibliographical note
Publisher Copyright:© 2024 ELRA Language Resource Association: CC BY-NC 4.0.
Keywords
- Abstract Meaning Representation
- annotation
- corpus creation
- cross-lingual parsing
- German