101 citations · 152 across the 18 of their papers we have counts for
21 papers
The DURel Annotation Tool: Human and Computational Measurement of Semantic Proximity, Sense Clusters and Semantic Change
Dominik Schlechtweg, Shafqat Mumtaz Virk, Pauline Sander +6
We present the DURel tool that implements the annotation of semantic proximity between uses of words into an online, open source interface. The tool supports standardized human ann…
LSCDiscovery: A shared task on semantic change discovery and detection in Spanish
Frank D. Zamora-Reina, Felipe Bravo-Marquez, Dominik Schlechtweg
We present the first shared task on semantic change discovery and detection in Spanish and create the first dataset of Spanish words manually annotated for semantic change using th…
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…
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…
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,…
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…
Effects of Pre- and Post-Processing on type-based Embeddings in Lexical Semantic Change Detection
Jens Kaiser, Sinan Kurtyigit, Serge Kotchourko +1
Lexical semantic change detection is a new and innovative research field. The optimal fine-tuning of models including pre- and post-processing is largely unclear. We optimize exist…
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…
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…
OP-IMS @ DIACR-Ita: Back to the Roots: SGNS+OP+CD still rocks Semantic Change Detection
Jens Kaiser, Dominik Schlechtweg, Sabine Schulte im Walde
We present the results of our participation in the DIACR-Ita shared task on lexical semantic change detection for Italian. We exploit one of the earliest and most influential seman…
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…
IMS at SemEval-2020 Task 1: How low can you go? Dimensionality in Lexical Semantic Change Detection
Jens Kaiser, Dominik Schlechtweg, Sean Papay +1
We present the results of our system for SemEval-2020 Task 1 that exploits a commonly used lexical semantic change detection model based on Skip-Gram with Negative Sampling. Our sy…
Simulating Lexical Semantic Change from Sense-Annotated Data
Dominik Schlechtweg, Sabine Schulte im Walde
We present a novel procedure to simulate lexical semantic change from synchronic sense-annotated data, and demonstrate its usefulness for assessing lexical semantic change detectio…
Shared task: Lexical semantic change detection in German (Student Project Report)
Adnan Ahmad, Kiflom Desta, Fabian Lang +1
Recent NLP architectures have illustrated in various ways how semantic change can be captured across time and domains. However, in terms of evaluation there is a lack of benchmarks…
A Wind of Change: Detecting and Evaluating Lexical Semantic Change across Times and Domains
Dominik Schlechtweg, Anna Hätty, Marco del Tredici +1
We perform an interdisciplinary large-scale evaluation for detecting lexical semantic divergences in a diachronic and in a synchronic task: semantic sense changes across time, and…
Second-order Co-occurrence Sensitivity of Skip-Gram with Negative Sampling
Dominik Schlechtweg, Cennet Oguz, Sabine Schulte im Walde
We simulate first- and second-order context overlap and show that Skip-Gram with Negative Sampling is similar to Singular Value Decomposition in capturing second-order co-occurrenc…
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…
Diachronic Usage Relatedness (DURel): A Framework for the Annotation of Lexical Semantic Change
Dominik Schlechtweg, Sabine Schulte im Walde, Stefanie Eckmann
We propose a framework that extends synchronic polysemy annotation to diachronic changes in lexical meaning, to counteract the lack of resources for evaluating computational models…
Distribution-based Prediction of the Degree of Grammaticalization for German Prepositions
Dominik Schlechtweg, Sabine Schulte im Walde
We test the hypothesis that the degree of grammaticalization of German prepositions correlates with their corpus-based contextual dispersion measured by word entropy. We find that…
German in Flux: Detecting Metaphoric Change via Word Entropy
Dominik Schlechtweg, Stefanie Eckmann, Enrico Santus +2
This paper explores the information-theoretic measure entropy to detect metaphoric change, transferring ideas from hypernym detection to research on language change. We also build…
Hypernyms under Siege: Linguistically-motivated Artillery for Hypernymy Detection
Vered Shwartz, Enrico Santus, Dominik Schlechtweg
The fundamental role of hypernymy in NLP has motivated the development of many methods for the automatic identification of this relation, most of which rely on word distribution. W…