@inproceedings{goldman-etal-2025-findings,
title = "Findings of the {U}ni{D}ive 2025 shared task on multilingual Morpho-Syntactic Parsing",
author = "Goldman, Omer and
Weissweiler, Leonie and
Acar, Kutay and
Alves, Diego and
Baczkowska, Anna and
Eryigit, Gulsen and
Krippnerov{\'a}, Lenka and
Pagano, Adriana and
Samard{\v{z}}i{\'c}, Tanja and
Talamo, Luigi and
Wr{\'o}blewska, Alina and
Zeman, Daniel and
Nivre, Joakim and
Tsarfay, Reut",
editor = "Goldman, Omer and
Weissweiler, Leonie and
Tsarfaty, Reut",
booktitle = "Proceedings of The UniDive 2025 Shared Task on Multilingual Morpho-Syntactic Parsing",
month = aug,
year = "2025",
address = "Ljubljana, Slovenia",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2025.unidive-1.1/",
pages = "1--18",
ISBN = "979-8-89176-320-3",
abstract = "This paper details the findings of the 2025 UniDive shared task on multilingual morphosyntactic parsing. It introduces a new representation in which morphology and syntax are modelled jointly to form dependency trees of contentful elements, each characterized by features determined by grammatical words and morphemes. This schema allows bypassing the theoretical debate over the definition of ``words'' and it encourages development of parsers for typologically diverse languages. The data for the task, spanning 9 languages, was annotated based on existing Universal Dependencies (UD) treebanks that were adapted to the new format. We accompany the data with a new metric, MSLAS, that combines syntactic LAS with F1 over grammatical features. The task received two submissions, which together with three baselines give a detailed view on the ability of multi-task encoder models to cope with the task at hand. The best performing system, UM, achieved 78.7 MSLAS macro-averaged over all languages, improving by 31.4 points over the few-shot prompting baseline."
}<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="goldman-etal-2025-findings">
<titleInfo>
<title>Findings of the UniDive 2025 shared task on multilingual Morpho-Syntactic Parsing</title>
</titleInfo>
<name type="personal">
<namePart type="given">Omer</namePart>
<namePart type="family">Goldman</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Leonie</namePart>
<namePart type="family">Weissweiler</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Kutay</namePart>
<namePart type="family">Acar</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Diego</namePart>
<namePart type="family">Alves</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Anna</namePart>
<namePart type="family">Baczkowska</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Gulsen</namePart>
<namePart type="family">Eryigit</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Lenka</namePart>
<namePart type="family">Krippnerová</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Adriana</namePart>
<namePart type="family">Pagano</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Tanja</namePart>
<namePart type="family">Samardžić</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Luigi</namePart>
<namePart type="family">Talamo</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Alina</namePart>
<namePart type="family">Wróblewska</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Daniel</namePart>
<namePart type="family">Zeman</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Joakim</namePart>
<namePart type="family">Nivre</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Reut</namePart>
<namePart type="family">Tsarfay</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<originInfo>
<dateIssued>2025-08</dateIssued>
</originInfo>
<typeOfResource>text</typeOfResource>
<relatedItem type="host">
<titleInfo>
<title>Proceedings of The UniDive 2025 Shared Task on Multilingual Morpho-Syntactic Parsing</title>
</titleInfo>
<name type="personal">
<namePart type="given">Omer</namePart>
<namePart type="family">Goldman</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Leonie</namePart>
<namePart type="family">Weissweiler</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Reut</namePart>
<namePart type="family">Tsarfaty</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<originInfo>
<publisher>Association for Computational Linguistics</publisher>
<place>
<placeTerm type="text">Ljubljana, Slovenia</placeTerm>
</place>
</originInfo>
<genre authority="marcgt">conference publication</genre>
<identifier type="isbn">979-8-89176-320-3</identifier>
</relatedItem>
<abstract>This paper details the findings of the 2025 UniDive shared task on multilingual morphosyntactic parsing. It introduces a new representation in which morphology and syntax are modelled jointly to form dependency trees of contentful elements, each characterized by features determined by grammatical words and morphemes. This schema allows bypassing the theoretical debate over the definition of “words” and it encourages development of parsers for typologically diverse languages. The data for the task, spanning 9 languages, was annotated based on existing Universal Dependencies (UD) treebanks that were adapted to the new format. We accompany the data with a new metric, MSLAS, that combines syntactic LAS with F1 over grammatical features. The task received two submissions, which together with three baselines give a detailed view on the ability of multi-task encoder models to cope with the task at hand. The best performing system, UM, achieved 78.7 MSLAS macro-averaged over all languages, improving by 31.4 points over the few-shot prompting baseline.</abstract>
<identifier type="citekey">goldman-etal-2025-findings</identifier>
<location>
<url>https://aclanthology.org/2025.unidive-1.1/</url>
</location>
<part>
<date>2025-08</date>
<extent unit="page">
<start>1</start>
<end>18</end>
</extent>
</part>
</mods>
</modsCollection>
%0 Conference Proceedings
%T Findings of the UniDive 2025 shared task on multilingual Morpho-Syntactic Parsing
%A Goldman, Omer
%A Weissweiler, Leonie
%A Acar, Kutay
%A Alves, Diego
%A Baczkowska, Anna
%A Eryigit, Gulsen
%A Krippnerová, Lenka
%A Pagano, Adriana
%A Samardžić, Tanja
%A Talamo, Luigi
%A Wróblewska, Alina
%A Zeman, Daniel
%A Nivre, Joakim
%A Tsarfay, Reut
%Y Goldman, Omer
%Y Weissweiler, Leonie
%Y Tsarfaty, Reut
%S Proceedings of The UniDive 2025 Shared Task on Multilingual Morpho-Syntactic Parsing
%D 2025
%8 August
%I Association for Computational Linguistics
%C Ljubljana, Slovenia
%@ 979-8-89176-320-3
%F goldman-etal-2025-findings
%X This paper details the findings of the 2025 UniDive shared task on multilingual morphosyntactic parsing. It introduces a new representation in which morphology and syntax are modelled jointly to form dependency trees of contentful elements, each characterized by features determined by grammatical words and morphemes. This schema allows bypassing the theoretical debate over the definition of “words” and it encourages development of parsers for typologically diverse languages. The data for the task, spanning 9 languages, was annotated based on existing Universal Dependencies (UD) treebanks that were adapted to the new format. We accompany the data with a new metric, MSLAS, that combines syntactic LAS with F1 over grammatical features. The task received two submissions, which together with three baselines give a detailed view on the ability of multi-task encoder models to cope with the task at hand. The best performing system, UM, achieved 78.7 MSLAS macro-averaged over all languages, improving by 31.4 points over the few-shot prompting baseline.
%U https://aclanthology.org/2025.unidive-1.1/
%P 1-18
Markdown (Informal)
[Findings of the UniDive 2025 shared task on multilingual Morpho-Syntactic Parsing](https://aclanthology.org/2025.unidive-1.1/) (Goldman et al., UNIDIVE-SyntaxFest 2025)
ACL
- Omer Goldman, Leonie Weissweiler, Kutay Acar, Diego Alves, Anna Baczkowska, Gulsen Eryigit, Lenka Krippnerová, Adriana Pagano, Tanja Samardžić, Luigi Talamo, Alina Wróblewska, Daniel Zeman, Joakim Nivre, and Reut Tsarfay. 2025. Findings of the UniDive 2025 shared task on multilingual Morpho-Syntactic Parsing. In Proceedings of The UniDive 2025 Shared Task on Multilingual Morpho-Syntactic Parsing, pages 1–18, Ljubljana, Slovenia. Association for Computational Linguistics.