activity
20162022
most citedSimulating Lexical Semantic Change from Sense-Annotated Data

15 citations · 23 across the 10 of their papers we have counts for

collaborators

21 papers

cs.CL2022

What Drives the Use of Metaphorical Language? Negative Insights from Abstractness, Affect, Discourse Coherence and Contextualized Word Representations

Prisca Piccirilli, Sabine Schulte im Walde

Given a specific discourse, which discourse properties trigger the use of metaphorical language, rather than using literal alternatives? For example, what drives people to say "gra…

cs.CL2022

Features of Perceived Metaphoricity on the Discourse Level: Abstractness and Emotionality

Prisca Piccirilli, Sabine Schulte im Walde

Research on metaphorical language has shown ties between abstractness and emotionality with regard to metaphoricity; prior work is however limited to the word and sentence levels,…

cs.CL2021

Lexical Semantic Change Discovery

Sinan Kurtyigit, Maike Park, Dominik Schlechtweg +2

While there is a large amount of research in the field of Lexical Semantic Change Detection, only few approaches go beyond a standard benchmark evaluation of existing models. In th…

cs.CL2021

More than just Frequency? Demasking Unsupervised Hypernymy Prediction Methods

Thomas Bott, Dominik Schlechtweg, Sabine Schulte im Walde

This paper presents a comparison of unsupervised methods of hypernymy prediction (i.e., to predict which word in a pair of words such as fish-cod is the hypernym and which the hypo…

cs.CL20211 cited

Explaining and Improving BERT Performance on Lexical Semantic Change Detection

Severin Laicher, Sinan Kurtyigit, Dominik Schlechtweg +2

Type- and token-based embedding architectures are still competing in lexical semantic change detection. The recent success of type-based models in SemEval-2020 Task 1 has raised th…

cs.CL20202 cited

CL-IMS @ DIACR-Ita: Volente o Nolente: BERT does not outperform SGNS on Semantic Change Detection

Severin Laicher, Gioia Baldissin, Enrique Castañeda +2

We present the results of our participation in the DIACR-Ita shared task on lexical semantic change detection for Italian. We exploit Average Pairwise Distance of token-based BERT…