@inproceedings{stepanek-etal-2025-comparing,
title = "Comparing Manual and Automatic {UMR}s for {C}zech and {L}atin",
author = "{\v{S}}t{\v{e}}p{\'a}nek, Jan and
Zeman, Daniel and
Lopatkov{\'a}, Mark{\'e}ta and
Gamba, Federica and
Hled{\'i}kov{\'a}, Hana",
editor = "Lai, Kenneth and
Wein, Shira",
booktitle = "Proceedings of the Sixth International Workshop on Designing Meaning Representations",
month = aug,
year = "2025",
address = "Prague, Czechia",
publisher = "Association for Computational Lingustics",
url = "https://aclanthology.org/2025.dmr-1.1/",
pages = "1--12",
abstract = "Uniform Meaning Representation (UMR) is a semantic framework designed to represent the meaning of texts in a structured and interpretable manner. In this paper, we evaluate the results of the automatic conversion of existing resources to UMR, focusing on Czech (PDT-C treebank) and Latin (LDT treebank). We present both quantitative and qualitative evaluations based on a comparison between manually and automatically generated UMR structures for a sample of Czech and Latin sentences. The findings indicate comparable results of the automatic conversion for both languages. The key challenges prove to be the higher level of semantic abstraction required by UMR and the fact that UMR allows for capturing semantic structure in multiple ways, potentially with varying levels of granularity."
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<abstract>Uniform Meaning Representation (UMR) is a semantic framework designed to represent the meaning of texts in a structured and interpretable manner. In this paper, we evaluate the results of the automatic conversion of existing resources to UMR, focusing on Czech (PDT-C treebank) and Latin (LDT treebank). We present both quantitative and qualitative evaluations based on a comparison between manually and automatically generated UMR structures for a sample of Czech and Latin sentences. The findings indicate comparable results of the automatic conversion for both languages. The key challenges prove to be the higher level of semantic abstraction required by UMR and the fact that UMR allows for capturing semantic structure in multiple ways, potentially with varying levels of granularity.</abstract>
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%0 Conference Proceedings
%T Comparing Manual and Automatic UMRs for Czech and Latin
%A Štěpánek, Jan
%A Zeman, Daniel
%A Lopatková, Markéta
%A Gamba, Federica
%A Hledíková, Hana
%Y Lai, Kenneth
%Y Wein, Shira
%S Proceedings of the Sixth International Workshop on Designing Meaning Representations
%D 2025
%8 August
%I Association for Computational Lingustics
%C Prague, Czechia
%F stepanek-etal-2025-comparing
%X Uniform Meaning Representation (UMR) is a semantic framework designed to represent the meaning of texts in a structured and interpretable manner. In this paper, we evaluate the results of the automatic conversion of existing resources to UMR, focusing on Czech (PDT-C treebank) and Latin (LDT treebank). We present both quantitative and qualitative evaluations based on a comparison between manually and automatically generated UMR structures for a sample of Czech and Latin sentences. The findings indicate comparable results of the automatic conversion for both languages. The key challenges prove to be the higher level of semantic abstraction required by UMR and the fact that UMR allows for capturing semantic structure in multiple ways, potentially with varying levels of granularity.
%U https://aclanthology.org/2025.dmr-1.1/
%P 1-12
Markdown (Informal)
[Comparing Manual and Automatic UMRs for Czech and Latin](https://aclanthology.org/2025.dmr-1.1/) (Štěpánek et al., DMR 2025)
ACL
- Jan Štěpánek, Daniel Zeman, Markéta Lopatková, Federica Gamba, and Hana Hledíková. 2025. Comparing Manual and Automatic UMRs for Czech and Latin. In Proceedings of the Sixth International Workshop on Designing Meaning Representations, pages 1–12, Prague, Czechia. Association for Computational Lingustics.