Jiamei Zeng
2026
From Categories to Decisions: A Framework for Attitudinal Analysis of Evaluative Language
Jiamei Zeng | Haitao Wang | Harry Bunt | Xinyu Cao | Min Dong | Tianyong Hao | Kiyong Lee | James Pustejovsky | Laurent Romary | Jianfang Zong | François Claude Rey | Sylviane Cardey | Yangli Jia | Shengqing Liao | Alex Chengyu Fang
Proceedings of the 22nd Joint ACL - ISO Workshop on Interoperable Semantic Annotation and Representation (ISA-22) @ LREC 2026
Jiamei Zeng | Haitao Wang | Harry Bunt | Xinyu Cao | Min Dong | Tianyong Hao | Kiyong Lee | James Pustejovsky | Laurent Romary | Jianfang Zong | François Claude Rey | Sylviane Cardey | Yangli Jia | Shengqing Liao | Alex Chengyu Fang
Proceedings of the 22nd Joint ACL - ISO Workshop on Interoperable Semantic Annotation and Representation (ISA-22) @ LREC 2026
The study reported in this paper aims to contribute to the development of an annotation scheme for evaluative language, based on Appraisal Theory, that addresses key sources of classification problems. In particular. it aims to develops a unified annotation scheme that proposes (1) a three-component annotation model comprising Appraiser, Appraised and Appraisal Element, (2) the operationalised distinction between Affect and Appreciation governed by a criterion of experiencer salience and a criterion distinguishing personal emotions from evaluations of conduct, and (3) a decision framework for the Judgement-Appreciation distinction structured on the target and lexis types operating through override conditions and substitution tests. The revised framework is illustrated with examples selected from a corpus of news discourse in English and is designed to be replicable across future Appraisal-based studies of evaluative language.
2025
Enhanced Evaluative Language Annotation through Refined Theoretical Framework and Workflow
Jiamei Zeng | Haitao Wang | Harry Bunt | Xinyu Cao | Sylviane Cardey | Min Dong | Tianyong Hao | Yangli Jia | Kiyong Lee | Shengqing Liao | James Pustejovsky | François Claude Rey | Laurent Romary | Jianfang Zong | Alex C. Fang
Proceedings of the 21st Joint ACL - ISO Workshop on Interoperable Semantic Annotation (ISA-21)
Jiamei Zeng | Haitao Wang | Harry Bunt | Xinyu Cao | Sylviane Cardey | Min Dong | Tianyong Hao | Yangli Jia | Kiyong Lee | Shengqing Liao | James Pustejovsky | François Claude Rey | Laurent Romary | Jianfang Zong | Alex C. Fang
Proceedings of the 21st Joint ACL - ISO Workshop on Interoperable Semantic Annotation (ISA-21)
As precursor work in preparation for an international standard ISO/PWI 24617-16 Language resource management – Semantic annotation – Part 16: Evaluative language, we aim to test and enhance the reliability of the annotation of subjective evaluation based on Appraisal Theory. We describe a comprehensive three-phase workflow tested on COVID-19 media reports to achieve reliable agreement through progressive training and quality control. Our methodology addresses some of the key challenges through the refinement of targeted guideline refinements and the development of interactive clarification tools, alongside a custom platform that enables the pre-classification of six evaluative categories, systematic annotation review, and organized documentation. We report empirical results that demonstrate substantial improvements from the initial moderate agreement to a strong final consensus. Our research offers both theoretical refinements addressing persistent classification challenges in evaluation and practical solutions for the implementation of the annotation workflow, proposing a replicable methodology for the achievement of reliable annotation consistency in the annotation of evaluative language.
2024
Annotating Evaluative Language: Challenges and Solutions in Applying Appraisal Theory
Jiamei Zeng | Min Dong | Alex Chengyu Fang
Proceedings of the 20th Joint ACL - ISO Workshop on Interoperable Semantic Annotation @ LREC-COLING 2024
Jiamei Zeng | Min Dong | Alex Chengyu Fang
Proceedings of the 20th Joint ACL - ISO Workshop on Interoperable Semantic Annotation @ LREC-COLING 2024
This article describes a corpus-based experiment to identify the challenges and solutions in the annotation of evaluative language according to the scheme defined in Appraisal Theory (Martin and White, 2005). Originating from systemic functional linguistics, Appraisal Theory provides a robust framework for the analysis of linguistic expressions of evaluation, stance, and interpersonal relationships. Despite its theoretical richness, the practical application of Appraisal Theory in text annotation presents significant challenges, chiefly due to the intricacies of identifying and classifying evaluative expressions within its sub-system of Attitude, which comprises Affect, Judgement, and Appreciation. This study examines these challenges through the annotation of a corpus of editorials related to the Russian-Ukraine conflict and aims to offer practical solutions to enhance the transparency and consistency of the annotation. By refining the annotation process and addressing the subjective nature in the identification and classification of evaluative language, this work represents some timely effort in the annotation of pragmatic knowledge in language resources.