@inproceedings{rim-etal-2026-qualia,
title = "A Qualia-Based Audit of Procedural Event Annotations",
author = "Rim, Kyeongmin and
Verhagen, Marc and
Pustejovsky, James",
editor = {H{\"u}rriyeto{\u{g}}lu, Ali and
Thapa, Surendrabikram and
Tanev, Hristo},
booktitle = "Proceedings of the 9th Workshop on Event Extraction and Understanding: Challenges and Applications ({EEUCA} 2026)",
month = jul,
year = "2026",
address = "San Diego, California, USA",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2026.eeuca-1.6/",
pages = "49--57",
ISBN = "979-8-89176-402-6",
abstract = "Procedural event annotations record *what changed* but not the semantic relevance or grounding of the change: whether the annotated entity is the kind of thing whose state matters for the domain.We present Entity Qualia Structure (EQS), a per-entity sortal-type categorization (coarsened from Generative Lexicon{'}s type system to three categories: natural, artifactual, instrument) extracted from existing lexical resources.Applied to the OpenPI food domain, EQS reaches 84.7{\%} coverage of the 518-item entity vocabulary; across 9367 transformation annotations, only 51.1{\%} concern food entities themselves, while 30.2{\%} record state changes of instruments, entities whose sortal type places them outside the food-state task.In a three-way comparison against existing cleanup efforts, EQS uniquely flags 15.6{\%} of annotations that neither human re-annotation (OpenPI-C) nor LLM salience scoring (OpenPI 2.0) catches.Analysis of the *agentive* quale reveals that 93{\%} of agentive-positive annotations involve instruments rather than food: entity creation can only be detected when the agentive feature is paired with the associated verb{'}s event semantics."
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<abstract>Procedural event annotations record *what changed* but not the semantic relevance or grounding of the change: whether the annotated entity is the kind of thing whose state matters for the domain.We present Entity Qualia Structure (EQS), a per-entity sortal-type categorization (coarsened from Generative Lexicon’s type system to three categories: natural, artifactual, instrument) extracted from existing lexical resources.Applied to the OpenPI food domain, EQS reaches 84.7% coverage of the 518-item entity vocabulary; across 9367 transformation annotations, only 51.1% concern food entities themselves, while 30.2% record state changes of instruments, entities whose sortal type places them outside the food-state task.In a three-way comparison against existing cleanup efforts, EQS uniquely flags 15.6% of annotations that neither human re-annotation (OpenPI-C) nor LLM salience scoring (OpenPI 2.0) catches.Analysis of the *agentive* quale reveals that 93% of agentive-positive annotations involve instruments rather than food: entity creation can only be detected when the agentive feature is paired with the associated verb’s event semantics.</abstract>
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%0 Conference Proceedings
%T A Qualia-Based Audit of Procedural Event Annotations
%A Rim, Kyeongmin
%A Verhagen, Marc
%A Pustejovsky, James
%Y Hürriyetoğlu, Ali
%Y Thapa, Surendrabikram
%Y Tanev, Hristo
%S Proceedings of the 9th Workshop on Event Extraction and Understanding: Challenges and Applications (EEUCA 2026)
%D 2026
%8 July
%I Association for Computational Linguistics
%C San Diego, California, USA
%@ 979-8-89176-402-6
%F rim-etal-2026-qualia
%X Procedural event annotations record *what changed* but not the semantic relevance or grounding of the change: whether the annotated entity is the kind of thing whose state matters for the domain.We present Entity Qualia Structure (EQS), a per-entity sortal-type categorization (coarsened from Generative Lexicon’s type system to three categories: natural, artifactual, instrument) extracted from existing lexical resources.Applied to the OpenPI food domain, EQS reaches 84.7% coverage of the 518-item entity vocabulary; across 9367 transformation annotations, only 51.1% concern food entities themselves, while 30.2% record state changes of instruments, entities whose sortal type places them outside the food-state task.In a three-way comparison against existing cleanup efforts, EQS uniquely flags 15.6% of annotations that neither human re-annotation (OpenPI-C) nor LLM salience scoring (OpenPI 2.0) catches.Analysis of the *agentive* quale reveals that 93% of agentive-positive annotations involve instruments rather than food: entity creation can only be detected when the agentive feature is paired with the associated verb’s event semantics.
%U https://aclanthology.org/2026.eeuca-1.6/
%P 49-57
Markdown (Informal)
[A Qualia-Based Audit of Procedural Event Annotations](https://aclanthology.org/2026.eeuca-1.6/) (Rim et al., EEUCA 2026)
ACL
- Kyeongmin Rim, Marc Verhagen, and James Pustejovsky. 2026. A Qualia-Based Audit of Procedural Event Annotations. In Proceedings of the 9th Workshop on Event Extraction and Understanding: Challenges and Applications (EEUCA 2026), pages 49–57, San Diego, California, USA. Association for Computational Linguistics.