@inproceedings{gehring-etal-2026-semeval,
title = "{S}em{E}val-2026 Task 5: Rating Plausibility of Word Senses in Ambiguous Stories through Narrative Understanding",
author = "Gehring, Janosch and
Meyer, Selina and
Roth, Michael",
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-1.448/",
pages = "3691--3703",
ISBN = "979-8-89176-414-9",
abstract = "We introduce SemEval-2026 Task 5 on ``Rating Plausibility of Word Senses in Ambiguous Stories through Narrative Understanding''. The dataset for this task consists of 4-5 sentence English short stories. In each story, one sentence includes a lexical ambiguity and different senses are to be judged in terms of plausibility on a Likert scale. The task is intentionally constructed to be challenging by stories only providing sparse contextual cues. We give an overview of well-performing, frequent and interesting approaches used by participating systems. From a total of 175 registered participants and 27 submitted system description papers, the best system achieved an ``accuracy within standard deviation'' score of 93.3{\%}."
}<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="gehring-etal-2026-semeval">
<titleInfo>
<title>SemEval-2026 Task 5: Rating Plausibility of Word Senses in Ambiguous Stories through Narrative Understanding</title>
</titleInfo>
<name type="personal">
<namePart type="given">Janosch</namePart>
<namePart type="family">Gehring</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Selina</namePart>
<namePart type="family">Meyer</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Michael</namePart>
<namePart type="family">Roth</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 introduce SemEval-2026 Task 5 on “Rating Plausibility of Word Senses in Ambiguous Stories through Narrative Understanding”. The dataset for this task consists of 4-5 sentence English short stories. In each story, one sentence includes a lexical ambiguity and different senses are to be judged in terms of plausibility on a Likert scale. The task is intentionally constructed to be challenging by stories only providing sparse contextual cues. We give an overview of well-performing, frequent and interesting approaches used by participating systems. From a total of 175 registered participants and 27 submitted system description papers, the best system achieved an “accuracy within standard deviation” score of 93.3%.</abstract>
<identifier type="citekey">gehring-etal-2026-semeval</identifier>
<location>
<url>https://aclanthology.org/2026.semeval-1.448/</url>
</location>
<part>
<date>2026-07</date>
<extent unit="page">
<start>3691</start>
<end>3703</end>
</extent>
</part>
</mods>
</modsCollection>
%0 Conference Proceedings
%T SemEval-2026 Task 5: Rating Plausibility of Word Senses in Ambiguous Stories through Narrative Understanding
%A Gehring, Janosch
%A Meyer, Selina
%A Roth, Michael
%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 gehring-etal-2026-semeval
%X We introduce SemEval-2026 Task 5 on “Rating Plausibility of Word Senses in Ambiguous Stories through Narrative Understanding”. The dataset for this task consists of 4-5 sentence English short stories. In each story, one sentence includes a lexical ambiguity and different senses are to be judged in terms of plausibility on a Likert scale. The task is intentionally constructed to be challenging by stories only providing sparse contextual cues. We give an overview of well-performing, frequent and interesting approaches used by participating systems. From a total of 175 registered participants and 27 submitted system description papers, the best system achieved an “accuracy within standard deviation” score of 93.3%.
%U https://aclanthology.org/2026.semeval-1.448/
%P 3691-3703
Markdown (Informal)
[SemEval-2026 Task 5: Rating Plausibility of Word Senses in Ambiguous Stories through Narrative Understanding](https://aclanthology.org/2026.semeval-1.448/) (Gehring et al., SemEval 2026)
ACL