@inproceedings{sabina-uban-etal-2022-black,
title = "{C}o{T}o{H}i{L}i at {LSCD}iscovery: the Role of Linguistic Features in Predicting Semantic Change",
author = "Sabina Uban, Ana and
Maria Cristea, Alina and
Daniela Dinu, Anca and
P Dinu, Liviu and
Georgescu, Simona and
Zoicas, Laurentiu",
editor = "Tahmasebi, Nina and
Montariol, Syrielle and
Kutuzov, Andrey and
Hengchen, Simon and
Dubossarsky, Haim and
Borin, Lars",
booktitle = "Proceedings of the 3rd Workshop on Computational Approaches to Historical Language Change",
month = may,
year = "2022",
address = "Dublin, Ireland",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2022.lchange-1.20",
doi = "10.18653/v1/2022.lchange-1.20",
pages = "187--192",
abstract = "This paper presents the contributions of the CoToHiLi team for the LSCDiscovery shared task on semantic change in the Spanish language. We participated in both tasks (graded discovery and binary change, including sense gain and sense loss) and proposed models based on word embedding distances combined with hand-crafted linguistic features, including polysemy, number of neological synonyms, and relation to cognates in English. We find that models that include linguistically informed features combined using weights assigned manually by experts lead to promising results.",
}
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%0 Conference Proceedings
%T CoToHiLi at LSCDiscovery: the Role of Linguistic Features in Predicting Semantic Change
%A Sabina Uban, Ana
%A Maria Cristea, Alina
%A Daniela Dinu, Anca
%A P Dinu, Liviu
%A Georgescu, Simona
%A Zoicas, Laurentiu
%Y Tahmasebi, Nina
%Y Montariol, Syrielle
%Y Kutuzov, Andrey
%Y Hengchen, Simon
%Y Dubossarsky, Haim
%Y Borin, Lars
%S Proceedings of the 3rd Workshop on Computational Approaches to Historical Language Change
%D 2022
%8 May
%I Association for Computational Linguistics
%C Dublin, Ireland
%F sabina-uban-etal-2022-black
%X This paper presents the contributions of the CoToHiLi team for the LSCDiscovery shared task on semantic change in the Spanish language. We participated in both tasks (graded discovery and binary change, including sense gain and sense loss) and proposed models based on word embedding distances combined with hand-crafted linguistic features, including polysemy, number of neological synonyms, and relation to cognates in English. We find that models that include linguistically informed features combined using weights assigned manually by experts lead to promising results.
%R 10.18653/v1/2022.lchange-1.20
%U https://aclanthology.org/2022.lchange-1.20
%U https://doi.org/10.18653/v1/2022.lchange-1.20
%P 187-192
Markdown (Informal)
[CoToHiLi at LSCDiscovery: the Role of Linguistic Features in Predicting Semantic Change](https://aclanthology.org/2022.lchange-1.20) (Sabina Uban et al., LChange 2022)
ACL