MultiCoS: A Multilingual Dataset of Connective Semantics with Context–Sentence Compatibility

Anne Mucha; Ciyang Qing; Wataru Uegaki

doi:10.63317/28ccty7yu9hn

MultiCoS: A Multilingual Dataset of Connective Semantics with Context–Sentence Compatibility

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Abstract

We present a multilingual dataset of connective semantics. The dataset contains the semantic annotations of clausal connectives (e.g. and and or in English) from 24 languages, based on our original native-speaker elicitation data. Unlike existing lexica on connectives, the dataset includes systematic evidence for the annotations in the form of context-sentence compatibility judgments, including negative evidence. The paper describes the methodology of data collection and the format of the dataset. We also discuss its potential use cases for the validation of cross-linguistic generalizations, examinations of their potential counterexamples, and for benchmarking felicity judgments by NLU systems.

Anthology ID:: 2026.lrec-1.381
Volume:: Proceedings of the Fifteenth Language Resources and Evaluation Conference
Month:: May
Year:: 2026
Address:: Palma de Mallorca, Spain
Editors:: Stelios Piperidis, Núria Bel, Henk van den Heuvel, Nancy Ide, Simon Krek, Antonio Toral
Venue:: LREC
SIG:
Publisher:: ELRA Language Resource Association
Note:
Pages:: 4861–4871
Language:
External URL:: https://lrec.elra.info/lrec2026-main-381
DOI:: 10.63317/28ccty7yu9hn
Bibkey:
Cite (ACL):: Anne Mucha, Ciyang Qing, and Wataru Uegaki. 2026. MultiCoS: A Multilingual Dataset of Connective Semantics with Context–Sentence Compatibility. In Proceedings of the Fifteenth Language Resources and Evaluation Conference, pages 4861–4871, Palma de Mallorca, Spain. ELRA Language Resource Association.
Cite (Informal):: MultiCoS: A Multilingual Dataset of Connective Semantics with Context–Sentence Compatibility (Mucha et al., LREC 2026)
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@inproceedings{mucha-etal-2026-multicos,
    title = "{M}ulti{C}o{S}: A Multilingual Dataset of Connective Semantics with Context{--}Sentence Compatibility",
    author = "Mucha, Anne  and
      Qing, Ciyang  and
      Uegaki, Wataru",
    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-1.381/",
    doi = "10.63317/28ccty7yu9hn",
    pages = "4861--4871",
    abstract = "We present a multilingual dataset of connective semantics. The dataset contains the semantic annotations of clausal connectives (e.g. and and or in English) from 24 languages, based on our original native-speaker elicitation data. Unlike existing lexica on connectives, the dataset includes systematic evidence for the annotations in the form of context-sentence compatibility judgments, including negative evidence. The paper describes the methodology of data collection and the format of the dataset. We also discuss its potential use cases for the validation of cross-linguistic generalizations, examinations of their potential counterexamples, and for benchmarking felicity judgments by NLU systems."
}

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%0 Conference Proceedings
%T MultiCoS: A Multilingual Dataset of Connective Semantics with Context–Sentence Compatibility
%A Mucha, Anne
%A Qing, Ciyang
%A Uegaki, Wataru
%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 mucha-etal-2026-multicos
%X We present a multilingual dataset of connective semantics. The dataset contains the semantic annotations of clausal connectives (e.g. and and or in English) from 24 languages, based on our original native-speaker elicitation data. Unlike existing lexica on connectives, the dataset includes systematic evidence for the annotations in the form of context-sentence compatibility judgments, including negative evidence. The paper describes the methodology of data collection and the format of the dataset. We also discuss its potential use cases for the validation of cross-linguistic generalizations, examinations of their potential counterexamples, and for benchmarking felicity judgments by NLU systems.
%R 10.63317/28ccty7yu9hn
%U https://aclanthology.org/2026.lrec-1.381/
%U https://doi.org/10.63317/28ccty7yu9hn
%P 4861-4871

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Markdown (Informal)

[MultiCoS: A Multilingual Dataset of Connective Semantics with Context–Sentence Compatibility](https://aclanthology.org/2026.lrec-1.381/) (Mucha et al., LREC 2026)

MultiCoS: A Multilingual Dataset of Connective Semantics with Context–Sentence Compatibility (Mucha et al., LREC 2026)

ACL

Anne Mucha, Ciyang Qing, and Wataru Uegaki. 2026. MultiCoS: A Multilingual Dataset of Connective Semantics with Context–Sentence Compatibility. In Proceedings of the Fifteenth Language Resources and Evaluation Conference, pages 4861–4871, Palma de Mallorca, Spain. ELRA Language Resource Association.