Annotation Uncertainty in the Context of Grammatical Change

TL;DR

This paper explores the sources and types of annotation uncertainty in large text corpora, especially for historical languages, aiming to unify perspectives from linguistics and computer science to improve annotation practices.

Contribution

It provides a detailed analysis of annotation uncertainty, identifying its sources and implications, and proposes a unified view to enhance collaboration between linguistics and computer science.

Findings

Identifies linguistic ambiguity as a key source of uncertainty

Highlights the impact of annotation expertise on data quality

Discusses practical implications for corpus annotation processes

Abstract

This paper elaborates on the notion of uncertainty in the context of annotation in large text corpora, specifically focusing on (but not limited to) historical languages. Such uncertainty might be due to inherent properties of the language, for example, linguistic ambiguity and overlapping categories of linguistic description, but could also be caused by lacking annotation expertise. By examining annotation uncertainty in more detail, we identify the sources and deepen our understanding of the nature and different types of uncertainty encountered in daily annotation practice. Moreover, some practical implications of our theoretical findings are also discussed. Last but not least, this article can be seen as an attempt to reconcile the perspectives of the main scientific disciplines involved in corpus projects, linguistics and computer science, to develop a unified view and to highlight the potential synergies between these disciplines.