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        <title>Three-part diachronic semantic change dataset for Russian</title>
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            <title>Proceedings of the 2nd International Workshop on Computational Approaches to Historical Language Change 2021</title>
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        <name type="personal">
            <namePart type="given">Nina</namePart>
            <namePart type="family">Tahmasebi</namePart>
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        <name type="personal">
            <namePart type="given">Adam</namePart>
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        <name type="personal">
            <namePart type="given">Yang</namePart>
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            <namePart type="given">Haim</namePart>
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    <abstract>We present a manually annotated lexical semantic change dataset for Russian: RuShiftEval. Its novelty is ensured by a single set of target words annotated for their diachronic semantic shifts across three time periods, while the previous work either used only two time periods, or different sets of target words. The paper describes the composition and annotation procedure for the dataset. In addition, it is shown how the ternary nature of RuShiftEval allows to trace specific diachronic trajectories: ‘changed at a particular time period and stable afterwards’ or ‘was changing throughout all time periods’. Based on the analysis of the submissions to the recent shared task on semantic change detection for Russian, we argue that correctly identifying such trajectories can be an interesting sub-task itself.</abstract>
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%0 Conference Proceedings
%T Three-part diachronic semantic change dataset for Russian
%A Kutuzov, Andrey
%A Pivovarova, Lidia
%Y Tahmasebi, Nina
%Y Jatowt, Adam
%Y Xu, Yang
%Y Hengchen, Simon
%Y Montariol, Syrielle
%Y Dubossarsky, Haim
%S Proceedings of the 2nd International Workshop on Computational Approaches to Historical Language Change 2021
%D 2021
%8 August
%I Association for Computational Linguistics
%C Online
%F kutuzov-pivovarova-2021-three
%X We present a manually annotated lexical semantic change dataset for Russian: RuShiftEval. Its novelty is ensured by a single set of target words annotated for their diachronic semantic shifts across three time periods, while the previous work either used only two time periods, or different sets of target words. The paper describes the composition and annotation procedure for the dataset. In addition, it is shown how the ternary nature of RuShiftEval allows to trace specific diachronic trajectories: ‘changed at a particular time period and stable afterwards’ or ‘was changing throughout all time periods’. Based on the analysis of the submissions to the recent shared task on semantic change detection for Russian, we argue that correctly identifying such trajectories can be an interesting sub-task itself.
%R 10.18653/v1/2021.lchange-1.2
%U https://aclanthology.org/2021.lchange-1.2/
%U https://doi.org/10.18653/v1/2021.lchange-1.2
%P 7-13

Markdown (Informal)

[Three-part diachronic semantic change dataset for Russian](https://aclanthology.org/2021.lchange-1.2/) (Kutuzov & Pivovarova, LChange 2021)

• Three-part diachronic semantic change dataset for Russian (Kutuzov & Pivovarova, LChange 2021)

ACL

• Andrey Kutuzov and Lidia Pivovarova. 2021. Three-part diachronic semantic change dataset for Russian. In Proceedings of the 2nd International Workshop on Computational Approaches to Historical Language Change 2021, pages 7–13, Online. Association for Computational Linguistics.