@inproceedings{kalo-2026-operationalization,
title = "Operationalization Is Part of the Claim: Operationalization-Aware Knowledge in the Era of Generated Answers",
author = "Kalo, Jan-Christoph",
editor = "Kalo, Jan-Christoph and
Nakashole, Ndapa and
Razniewski, Simon and
Suchanek, Fabian M. and
Vlachos, Andreas and
McCallum, Andrew",
booktitle = "Proceedings of the 11th Workshop on Automated Knowledge Base Construction ({AKBC} 2026)",
month = oct,
year = "2026",
address = "Budapest, Hungary",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2026.akbc-1.20/",
pages = "284--292",
ISBN = "979-8-89176-464-4",
abstract = "LLM-based systems increasingly search across sources and synthesize numerical findings, but can treat values from different sources as directly comparable. The same phenomenon may be measured by defining the quantity differently or by estimating it through different procedures. Together, these choices form a value{'}s operationalization. Values produced under different operationalizations can differ without creating a factual conflict. Ignoring such differences can lead systems to make unsupported comparisons or combinations, or to present one result as the single correct answer even though the appropriate choice depends on the user{'}s purpose. We call this operationalization collapse. This vision paper argues that operationalization is part of a numerical claim, not optional metadata. Operationalization information can show what a value means and which comparisons or combinations it supports, but it may not determine which valid result should be used to answer the user{'}s question. We outline a research program for recovering operationalizations, attaching them to claims, determining which comparisons and combinations those claims support, and generating answers that preserve unresolved choices."
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<abstract>LLM-based systems increasingly search across sources and synthesize numerical findings, but can treat values from different sources as directly comparable. The same phenomenon may be measured by defining the quantity differently or by estimating it through different procedures. Together, these choices form a value’s operationalization. Values produced under different operationalizations can differ without creating a factual conflict. Ignoring such differences can lead systems to make unsupported comparisons or combinations, or to present one result as the single correct answer even though the appropriate choice depends on the user’s purpose. We call this operationalization collapse. This vision paper argues that operationalization is part of a numerical claim, not optional metadata. Operationalization information can show what a value means and which comparisons or combinations it supports, but it may not determine which valid result should be used to answer the user’s question. We outline a research program for recovering operationalizations, attaching them to claims, determining which comparisons and combinations those claims support, and generating answers that preserve unresolved choices.</abstract>
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%0 Conference Proceedings
%T Operationalization Is Part of the Claim: Operationalization-Aware Knowledge in the Era of Generated Answers
%A Kalo, Jan-Christoph
%Y Kalo, Jan-Christoph
%Y Nakashole, Ndapa
%Y Razniewski, Simon
%Y Suchanek, Fabian M.
%Y Vlachos, Andreas
%Y McCallum, Andrew
%S Proceedings of the 11th Workshop on Automated Knowledge Base Construction (AKBC 2026)
%D 2026
%8 October
%I Association for Computational Linguistics
%C Budapest, Hungary
%@ 979-8-89176-464-4
%F kalo-2026-operationalization
%X LLM-based systems increasingly search across sources and synthesize numerical findings, but can treat values from different sources as directly comparable. The same phenomenon may be measured by defining the quantity differently or by estimating it through different procedures. Together, these choices form a value’s operationalization. Values produced under different operationalizations can differ without creating a factual conflict. Ignoring such differences can lead systems to make unsupported comparisons or combinations, or to present one result as the single correct answer even though the appropriate choice depends on the user’s purpose. We call this operationalization collapse. This vision paper argues that operationalization is part of a numerical claim, not optional metadata. Operationalization information can show what a value means and which comparisons or combinations it supports, but it may not determine which valid result should be used to answer the user’s question. We outline a research program for recovering operationalizations, attaching them to claims, determining which comparisons and combinations those claims support, and generating answers that preserve unresolved choices.
%U https://aclanthology.org/2026.akbc-1.20/
%P 284-292
Markdown (Informal)
[Operationalization Is Part of the Claim: Operationalization-Aware Knowledge in the Era of Generated Answers](https://aclanthology.org/2026.akbc-1.20/) (Kalo, AKBC 2026)
ACL