DWUG: A large Resource of Diachronic Word Usage Graphs in Four Languages

TL;DR

This paper introduces DWUG, the largest resource of diachronic word usage graphs across four languages, created through extensive human annotations and clustering methods, enabling better understanding of word meaning changes over time.

Contribution

The paper presents a novel large-scale dataset of diachronic word usage graphs with human annotations, covering four languages, and details the annotation and clustering methodology.

Findings

Created a dataset with 100,000 human semantic judgments

Developed a clustering algorithm for grouping usages into senses

Discussed potential diachronic and synchronic applications

Abstract

Word meaning is notoriously difficult to capture, both synchronically and diachronically. In this paper, we describe the creation of the largest resource of graded contextualized, diachronic word meaning annotation in four different languages, based on 100,000 human semantic proximity judgments. We thoroughly describe the multi-round incremental annotation process, the choice for a clustering algorithm to group usages into senses, and possible - diachronic and synchronic - uses for this dataset.