101 citations · 202 across the 6 of their papers we have counts for
7 papers
SuperSim: a test set for word similarity and relatedness in Swedish
Simon Hengchen, Nina Tahmasebi
Language models are notoriously difficult to evaluate. We release SuperSim, a large-scale similarity and relatedness test set for Swedish built with expert human judgments. The tes…
DWUG: A large Resource of Diachronic Word Usage Graphs in Four Languages
Dominik Schlechtweg, Nina Tahmasebi, Simon Hengchen +2
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,…
Challenges for Computational Lexical Semantic Change
Simon Hengchen, Nina Tahmasebi, Dominik Schlechtweg +1
The computational study of lexical semantic change (LSC) has taken off in the past few years and we are seeing increasing interest in the field, from both computational sciences an…
SemEval-2020 Task 1: Unsupervised Lexical Semantic Change Detection
Dominik Schlechtweg, Barbara McGillivray, Simon Hengchen +2
Lexical Semantic Change detection, i.e., the task of identifying words that change meaning over time, is a very active research area, with applications in NLP, lexicography, and li…
Time-Out: Temporal Referencing for Robust Modeling of Lexical Semantic Change
Haim Dubossarsky, Simon Hengchen, Nina Tahmasebi +1
State-of-the-art models of lexical semantic change detection suffer from noise stemming from vector space alignment. We have empirically tested the Temporal Referencing method for…
Survey of Computational Approaches to Lexical Semantic Change
Nina Tahmasebi, Lars Borin, Adam Jatowt
Our languages are in constant flux driven by external factors such as cultural, societal and technological changes, as well as by only partially understood internal motivations. Wo…
Named Entity Evolution Recognition on the Blogosphere
Helge Holzmann, Nina Tahmasebi, Thomas Risse
Advancements in technology and culture lead to changes in our language. These changes create a gap between the language known by users and the language stored in digital archives.…