U ni T : One Document, Many Revisions, Too Many Edit Intention Taxonomies (2025)

Abstract: Writing is inherently iterative, each revision enhancing information representation. One revision may contain many edits. Examination of the intentions behind edits provides valuable insights into an editor’s expertise, the dynamics of collaborative writing, and the evolution of a document. Current research on edit intentions lacks a comprehensive edit intention taxonomy (EIT) that spans multiple application domains. As a result, researchers often create new EITs tailored to specific needs, a process that is both time-consuming and costly. To address this gap, we propose UniT, a Unified edit intention Taxonomy that integrates existing EITs encompassing a wide range of edit intentions. We examine the lineage relationship and the construction of 24 EITs. They together have 232 categories across various domains. During the literature survey and integration process, we identify challenges such as one-to-many category matches, incomplete definitions, and varying hierarchical structures. We propose solutions for resolving these issues. Finally, our evaluation shows that our UniT achieves higher inter-annotator agreement scores compared to existing EITs and is applicable to a large set of application domains.

## introduction text is an important medium for sharing information, whether it is reporting news @xcite , documenting scientific discoveries, or narrating stories. writing is an iterative process that involves revising text to improve how information is conveyed. one revision is created when an editor saves changes to the current document, potentially including multiple local edits @xcite . a single document may undergo multiple revisions. studying these revisions and the intentions behind them offers significant value in natural language processing tasks @xcite @xcite . for instance, analyzing stylistic edits in writing not only helps identify grammatical errors but also provides insight into the structure of arguments and the overall design of the text @xcite @xcite . revisions may be grouped in patterns and the relationship between the patterns can inform about an editor's level of writing experience @xcite . in addition, the analysis of intentions enables the creation of assistive tools, such as recommender systems for the collaborative writing @xcite . for lengthy documents such as laws, user agreements, and software manual, quickly identifying revisions and understanding their purpose can reduce reading time, enabling readers to focus on the most relevant sections without having to review the entire document. current studies tend to focus on single domains, such as collaborative authoring @xcite , informative writing @xcite , journalistic writing @xcite , and source code @xcite . other works study certain aspects of editing revisions, such as style, syntax @xcite , semantics analysis @xcite , and the edits objects analysis @xcite . a pattern observed in the literature is that when researchers need to analyze revision intentions in a new domain, they develop a new eit either by building it from scratch or adapting an existing one, incurring time and potential financial cost. we develop a comprehensive eit that spans multiple application domains and encompasses all observed edit intentions, reducing the burden to create a new eit for each application. this can be achieved either by constructing the eit from scratch or by leveraging existing ones. we opt for the latter because jointly existing eits cover multiple application domains, have a large number of edit (sub)categories, and include many edit intentions. in this paper, we report our work on creating unit, a unified and comprehensive eit, by painstakingly studying and integrating all foot_1 existing eits. thus, users aiming to develop a new eit tailored to their specific task can simply select a subset of edit intentions from our unit without the need to search through multiple existing eits. ## grouping eits based on lineage the previous section outlines the contributions of past work on eits. here, we examine the relationships between eits by analyzing the citation network among the reviewed papers, which reveals a lineage network among eits, e.g., one eit builds upon another by performing changes, such as category merging or splitting. we describe this network in this section and use it in the next section to group eits. then we proceed with integration of eits by groups. figure 3 outlines the lineage. ## taxonomy integration we define the eit integration task as follows: given a set of eits, generate a single integrated eit that includes all the categories from the individual eits, subject to certain modifications. this section discusses the process of eit integration, including matching (appendix a.7 gives partial matching results), merging, as well as adding revision examples (naming and adding definitions are covered in appendix a.4 and a.5). ## evaluation to evaluate our unit, we ask two questions: rq1 does the use of unit result in better annotator agreement compared to other eits? rq2 does unit perform consistently across datasets from varied domains? ## conclusion this work addresses the need for a comprehensive and unified eit across multiple domains by integrating existing eits into a large, cohesive framework. our research resolves the inconsistencies and ambiguities inherent in previous works. the proposed eit, unit, not only spans diverse application domains but also considers various analytical aspects, making it highly applicable for human annotators. evaluation results demonstrate that the integrated taxonomy is more applicable to human annotators by comparing iaa scores among annotators with different eits. future research should focus on applying the unit to new application domains. we believe its extensibility and adaptability make it a robust tool for future research.