@inproceedings{mitov-etal-2026-amr,
title = "{AMR} Parsing beyond {E}nglish: An Experiment on {B}ulgarian, {F}rench, {H}ungarian and {U}krainian",
author = "Mitov, Ivaylo and
Marharian, Tadzhat and
Hauk, Zsofia F. and
FALL, Samba and
Amblard, Maxime and
Guillaume, Bruno",
editor = "Piperidis, Stelios and
Bel, N{\'u}ria and
van den Heuvel, Henk and
Ide, Nancy and
Krek, Simon and
Toral, Antonio",
booktitle = "Proceedings of the Fifteenth Language Resources and Evaluation Conference",
month = may,
year = "2026",
address = "Palma de Mallorca, Spain",
publisher = "ELRA Language Resource Association",
url = "https://aclanthology.org/2026.lrec-1.764/",
doi = "10.63317/2qb7sj4u3jn4",
pages = "9733--9744",
abstract = "Under the assumption that the meaning of a sentence should be unchanged when it is translated into another language, recent work has developed on cross-lingual semantic parsing in an effort to extend the access to semantic resources beyond English. In this paper, we develop the automatic production of Abstract Meaning Representations (AMR), a graph-based semantic formalism, for four languages {--} Bulgarian, French, Hungarian and Ukrainian. We achieve high-performance on French and Hungarian, and execute, to our knowledge, the first semantic parsing of Bulgarian and Ukrainian on translations of the AMR3.0 corpus (Knight et al., 2020). Furthermore, we perform a complementary experiment on a novel parallel corpus of gold AMR annotations of the first chapter of ``The Adventures of Pinocchio'' in Bulgarian and Ukrainian. The experiment reveals that, despite their above-average performance, the models' performance decreases when probed on texts outside of the domain of the training data."
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<abstract>Under the assumption that the meaning of a sentence should be unchanged when it is translated into another language, recent work has developed on cross-lingual semantic parsing in an effort to extend the access to semantic resources beyond English. In this paper, we develop the automatic production of Abstract Meaning Representations (AMR), a graph-based semantic formalism, for four languages – Bulgarian, French, Hungarian and Ukrainian. We achieve high-performance on French and Hungarian, and execute, to our knowledge, the first semantic parsing of Bulgarian and Ukrainian on translations of the AMR3.0 corpus (Knight et al., 2020). Furthermore, we perform a complementary experiment on a novel parallel corpus of gold AMR annotations of the first chapter of “The Adventures of Pinocchio” in Bulgarian and Ukrainian. The experiment reveals that, despite their above-average performance, the models’ performance decreases when probed on texts outside of the domain of the training data.</abstract>
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%0 Conference Proceedings
%T AMR Parsing beyond English: An Experiment on Bulgarian, French, Hungarian and Ukrainian
%A Mitov, Ivaylo
%A Marharian, Tadzhat
%A Hauk, Zsofia F.
%A FALL, Samba
%A Amblard, Maxime
%A Guillaume, Bruno
%Y Piperidis, Stelios
%Y Bel, Núria
%Y van den Heuvel, Henk
%Y Ide, Nancy
%Y Krek, Simon
%Y Toral, Antonio
%S Proceedings of the Fifteenth Language Resources and Evaluation Conference
%D 2026
%8 May
%I ELRA Language Resource Association
%C Palma de Mallorca, Spain
%F mitov-etal-2026-amr
%X Under the assumption that the meaning of a sentence should be unchanged when it is translated into another language, recent work has developed on cross-lingual semantic parsing in an effort to extend the access to semantic resources beyond English. In this paper, we develop the automatic production of Abstract Meaning Representations (AMR), a graph-based semantic formalism, for four languages – Bulgarian, French, Hungarian and Ukrainian. We achieve high-performance on French and Hungarian, and execute, to our knowledge, the first semantic parsing of Bulgarian and Ukrainian on translations of the AMR3.0 corpus (Knight et al., 2020). Furthermore, we perform a complementary experiment on a novel parallel corpus of gold AMR annotations of the first chapter of “The Adventures of Pinocchio” in Bulgarian and Ukrainian. The experiment reveals that, despite their above-average performance, the models’ performance decreases when probed on texts outside of the domain of the training data.
%R 10.63317/2qb7sj4u3jn4
%U https://aclanthology.org/2026.lrec-1.764/
%U https://doi.org/10.63317/2qb7sj4u3jn4
%P 9733-9744
Markdown (Informal)
[AMR Parsing beyond English: An Experiment on Bulgarian, French, Hungarian and Ukrainian](https://aclanthology.org/2026.lrec-1.764/) (Mitov et al., LREC 2026)
ACL
- Ivaylo Mitov, Tadzhat Marharian, Zsofia F. Hauk, Samba FALL, Maxime Amblard, and Bruno Guillaume. 2026. AMR Parsing beyond English: An Experiment on Bulgarian, French, Hungarian and Ukrainian. In Proceedings of the Fifteenth Language Resources and Evaluation Conference, pages 9733–9744, Palma de Mallorca, Spain. ELRA Language Resource Association.