BibTeX

@inProceedings{skoldberg-etal-2024-revealing-341866,
	title        = {Revealing Semantic Variation in Swedish Using Computational Models of
Semantic Proximity–Results From Lexicographical Experiments},
	abstract     = {The paper reports a pilot study on the detection of lexical semantic variation in
modern Swedish. The starting point of the study is the meaning descriptions of around 65,000
headwords in ’The Contemporary Dictionary of the Swedish Academy’ (SO, 2021) covering
approximately 100,000 different senses. In our work, we aim to explore the potential of the
latest computational methods to discover outdated definitions in SO and update them. For
this, we make use of the DURel tool (Schlechtweg et al., 2018, 2024) which relies on state-
of-the-art language models for the automatic semantic analysis of word usages. The work
resulted in drawing lexicographers’ attention to both main senses and subsenses that should
be added to the dictionary. It has also demonstrated that certain meaning descriptions in SO
are too general and should be split in accordance with the current principles for the semantic
descriptions in the dictionary.},
	booktitle    = {Lexicography and Semantics. Proceedings of the XXI EURALEX International Congress 8–12 October 2024 Cavtat, Croatia (eds. Kristina Š. Despot, Ana Ostroški Anić & Ivana Brač )},
	author       = {Sköldberg, Emma and Virk, Shafqat and Sander, Pauline and Hengchen, Simon and Schlechtweg, Dominik},
	year         = {2024},
	publisher    = {Institut za hrvatski jezik},
	ISBN         = {978‐953‐7967‐77‐2},
}

@inProceedings{schlechtweg-etal-2024-durel-336715,
	title        = {The DURel Annotation Tool: Human and Computational Measurement of Semantic Proximity, Sense Clusters and Semantic Change},
	abstract     = {We present the DURel tool implementing the annotation of semantic proximity between word uses into an online, open source interface. The tool supports standardized human annotation as well as computational annotation, building on recent advances with Word-in-Context models. Annotator judgments are clustered with automatic graph clustering techniques and visualized for analysis. This allows to measure word senses with simple and intuitive micro-task judgments between use pairs, requiring minimal preparation efforts. The tool offers additional functionalities to compare the agreement between annotators to guarantee the inter-subjectivity of the obtained judgments and to calculate summary statistics over the annotated data giving insights into sense frequency distributions, semantic variation or changes of senses over time.},
	booktitle    = {Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics: System Demonstrations, March 17-22, 2024, St. Julians, Malta. },
	author       = {Schlechtweg, Dominik and Virk, Shafqat and Sander, Pauline and Sköldberg, Emma and Theuer Linke, Lukas and Zhang, Tuo and Tahmasebi, Nina and Schulte im Walde, Sabine},
	year         = {2024},
	publisher    = {Association for Computational Linguistics},
	ISBN         = {979-8-89176-091-2},
}

@inProceedings{sander-etal-2024-durel-341867,
	title        = {The DURel Annotation Tool},
	booktitle    = {Book of Abstracts of the Workshop Large Language Models and Lexicography, 8 October 2024 Cavtat, Croatia (ed. Simon Krek)},
	author       = {Sander, Pauline and Hengchen, Simon and Zhao, Wei and Ma, Xiaocheng and Sköldberg, Emma and Virk, Shafqat and Schlechtweg, Dominik},
	year         = {2024},
}