UAlberta at SemEval-2026 Task 5: Disambiguating Stories via Task Decomposition

David Basil; Junhyeon Cho; Chirooth Girigowda; Guoqing Luo; Sahir Momin; Sevryn Robinson; Ning Shi; Grzegorz Kondrak

UAlberta at SemEval-2026 Task 5: Disambiguating Stories via Task Decomposition

David Basil, Junhyeon Cho, Chirooth Girigowda, Guoqing Luo, Sahir Momin, Sevryn Robinson, Ning Shi, Grzegorz Kondrak

Correct Metadata for

Use this form to create a GitHub issue with structured data describing the correction. You will need a GitHub account. Once you create that issue, the correction will be reviewed by a staff member.

⚠️ Mobile Users: Submitting this form to create a new issue will only work with github.com, not the GitHub Mobile app.

Important: The Anthology treat PDFs as authoritative. Please use this form only to correct data that is out of line with the PDF. See our corrections guidelines if you need to change the PDF.

Title Adjust the title. Retain tags such as <fixed-case>.

Authors Adjust author names and order to match the PDF.

Abstract Correct abstract if needed. Retain XML formatting tags such as <tex-math>. You may use <b>...</b> for bold, <i>...</i> for italic, and <url>...</url> for URLs.

Verification against PDF Ensure that the new title/authors match the snapshot below. (If there is no snapshot or it is too small, consult the PDF.)

Authors concatenated from the text boxes above:

ALL author names match the snapshot above—including middle initials, hyphens, and accents.

Abstract

We describe our system for predicting sense plausibility in short narratives. Our approach centers on task decomposition: instead of predicting a score directly, we break the problem into simpler subtasks and combine their outputs. We further improve performance by ensembling complementary signals, including word sense disambiguation and fine-tuned embedding models. We also find empirical support for the one-homonym-per-translation principle of Hauer and Kondrak (2020a). Our best ensemble system achieves competitive performance in the official evaluation. Our code and data are available on GitHub.

Anthology ID:: 2026.semeval-1.340
Volume:: Proceedings of the 20th International Workshop on Semantic Evaluation (2026)
Month:: July
Year:: 2026
Address:: San Diego, California, USA
Editors:: Ekaterina Kochmar, Debanjan Ghosh, Kai North, Mamoru Komachi
Venues:: SemEval | WS
SIG:
Publisher:: Association for Computational Linguistics
Note:
Pages:: 2697–2708
Language:
URL:: https://aclanthology.org/2026.semeval-1.340/
DOI:
Bibkey:
Cite (ACL):: David Basil, Junhyeon Cho, Chirooth Girigowda, Guoqing Luo, Sahir Momin, Sevryn Robinson, Ning Shi, and Grzegorz Kondrak. 2026. UAlberta at SemEval-2026 Task 5: Disambiguating Stories via Task Decomposition. In Proceedings of the 20th International Workshop on Semantic Evaluation (2026), pages 2697–2708, San Diego, California, USA. Association for Computational Linguistics.
Cite (Informal):: UAlberta at SemEval-2026 Task 5: Disambiguating Stories via Task Decomposition (Basil et al., SemEval 2026)
Copy Citation:
PDF:: https://aclanthology.org/2026.semeval-1.340.pdf

PDF Cite Search Fix data

Export citation

BibTeX
MODS XML
Endnote
Preformatted

@inproceedings{basil-etal-2026-ualberta,
    title = "{UA}lberta at {S}em{E}val-2026 Task 5: Disambiguating Stories via Task Decomposition",
    author = "Basil, David  and
      Cho, Junhyeon  and
      Girigowda, Chirooth  and
      Luo, Guoqing  and
      Momin, Sahir  and
      Robinson, Sevryn  and
      Shi, Ning  and
      Kondrak, Grzegorz",
    editor = "Kochmar, Ekaterina  and
      Ghosh, Debanjan  and
      North, Kai  and
      Komachi, Mamoru",
    booktitle = "Proceedings of the 20th {I}nternational {W}orkshop on {S}emantic {E}valuation (2026)",
    month = jul,
    year = "2026",
    address = "San Diego, California, USA",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2026.semeval-1.340/",
    pages = "2697--2708",
    ISBN = "979-8-89176-414-9",
    abstract = "We describe our system for predicting sense plausibility in short narratives. Our approach centers on task decomposition: instead of predicting a score directly, we break the problem into simpler subtasks and combine their outputs. We further improve performance by ensembling complementary signals, including word sense disambiguation and fine-tuned embedding models. We also find empirical support for the one-homonym-per-translation principle of Hauer and Kondrak (2020a). Our best ensemble system achieves competitive performance in the official evaluation. Our code and data are available on GitHub."
}

Download as File

<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="basil-etal-2026-ualberta">
    <titleInfo>
        <title>UAlberta at SemEval-2026 Task 5: Disambiguating Stories via Task Decomposition</title>
    </titleInfo>
    <name type="personal">
        <namePart type="given">David</namePart>
        <namePart type="family">Basil</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Junhyeon</namePart>
        <namePart type="family">Cho</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Chirooth</namePart>
        <namePart type="family">Girigowda</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Guoqing</namePart>
        <namePart type="family">Luo</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Sahir</namePart>
        <namePart type="family">Momin</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Sevryn</namePart>
        <namePart type="family">Robinson</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Ning</namePart>
        <namePart type="family">Shi</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Grzegorz</namePart>
        <namePart type="family">Kondrak</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <originInfo>
        <dateIssued>2026-07</dateIssued>
    </originInfo>
    <typeOfResource>text</typeOfResource>
    <relatedItem type="host">
        <titleInfo>
            <title>Proceedings of the 20th International Workshop on Semantic Evaluation (2026)</title>
        </titleInfo>
        <name type="personal">
            <namePart type="given">Ekaterina</namePart>
            <namePart type="family">Kochmar</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Debanjan</namePart>
            <namePart type="family">Ghosh</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Kai</namePart>
            <namePart type="family">North</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Mamoru</namePart>
            <namePart type="family">Komachi</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <originInfo>
            <publisher>Association for Computational Linguistics</publisher>
            <place>
                <placeTerm type="text">San Diego, California, USA</placeTerm>
            </place>
        </originInfo>
        <genre authority="marcgt">conference publication</genre>
        <identifier type="isbn">979-8-89176-414-9</identifier>
    </relatedItem>
    <abstract>We describe our system for predicting sense plausibility in short narratives. Our approach centers on task decomposition: instead of predicting a score directly, we break the problem into simpler subtasks and combine their outputs. We further improve performance by ensembling complementary signals, including word sense disambiguation and fine-tuned embedding models. We also find empirical support for the one-homonym-per-translation principle of Hauer and Kondrak (2020a). Our best ensemble system achieves competitive performance in the official evaluation. Our code and data are available on GitHub.</abstract>
    <identifier type="citekey">basil-etal-2026-ualberta</identifier>
    <location>
        <url>https://aclanthology.org/2026.semeval-1.340/</url>
    </location>
    <part>
        <date>2026-07</date>
        <extent unit="page">
            <start>2697</start>
            <end>2708</end>
        </extent>
    </part>
</mods>
</modsCollection>

Download as File

%0 Conference Proceedings
%T UAlberta at SemEval-2026 Task 5: Disambiguating Stories via Task Decomposition
%A Basil, David
%A Cho, Junhyeon
%A Girigowda, Chirooth
%A Luo, Guoqing
%A Momin, Sahir
%A Robinson, Sevryn
%A Shi, Ning
%A Kondrak, Grzegorz
%Y Kochmar, Ekaterina
%Y Ghosh, Debanjan
%Y North, Kai
%Y Komachi, Mamoru
%S Proceedings of the 20th International Workshop on Semantic Evaluation (2026)
%D 2026
%8 July
%I Association for Computational Linguistics
%C San Diego, California, USA
%@ 979-8-89176-414-9
%F basil-etal-2026-ualberta
%X We describe our system for predicting sense plausibility in short narratives. Our approach centers on task decomposition: instead of predicting a score directly, we break the problem into simpler subtasks and combine their outputs. We further improve performance by ensembling complementary signals, including word sense disambiguation and fine-tuned embedding models. We also find empirical support for the one-homonym-per-translation principle of Hauer and Kondrak (2020a). Our best ensemble system achieves competitive performance in the official evaluation. Our code and data are available on GitHub.
%U https://aclanthology.org/2026.semeval-1.340/
%P 2697-2708

Download as File

Markdown (Informal)

[UAlberta at SemEval-2026 Task 5: Disambiguating Stories via Task Decomposition](https://aclanthology.org/2026.semeval-1.340/) (Basil et al., SemEval 2026)

UAlberta at SemEval-2026 Task 5: Disambiguating Stories via Task Decomposition (Basil et al., SemEval 2026)

ACL

David Basil, Junhyeon Cho, Chirooth Girigowda, Guoqing Luo, Sahir Momin, Sevryn Robinson, Ning Shi, and Grzegorz Kondrak. 2026. UAlberta at SemEval-2026 Task 5: Disambiguating Stories via Task Decomposition. In Proceedings of the 20th International Workshop on Semantic Evaluation (2026), pages 2697–2708, San Diego, California, USA. Association for Computational Linguistics.