@inproceedings{koper-schulte-im-walde-2018-analogies,
title = "Analogies in Complex Verb Meaning Shifts: the Effect of Affect in Semantic Similarity Models",
author = {K{\"o}per, Maximilian and
Schulte im Walde, Sabine},
editor = "Walker, Marilyn and
Ji, Heng and
Stent, Amanda",
booktitle = "Proceedings of the 2018 Conference of the North {A}merican Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 2 (Short Papers)",
month = jun,
year = "2018",
address = "New Orleans, Louisiana",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/N18-2024",
doi = "10.18653/v1/N18-2024",
pages = "150--156",
abstract = "We present a computational model to detect and distinguish analogies in meaning shifts between German base and complex verbs. In contrast to corpus-based studies, a novel dataset demonstrates that {``}regular{''} shifts represent the smallest class. Classification experiments relying on a standard similarity model successfully distinguish between four types of shifts, with verb classes boosting the performance, and affective features for abstractness, emotion and sentiment representing the most salient indicators.",
}
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%0 Conference Proceedings
%T Analogies in Complex Verb Meaning Shifts: the Effect of Affect in Semantic Similarity Models
%A Köper, Maximilian
%A Schulte im Walde, Sabine
%Y Walker, Marilyn
%Y Ji, Heng
%Y Stent, Amanda
%S Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 2 (Short Papers)
%D 2018
%8 June
%I Association for Computational Linguistics
%C New Orleans, Louisiana
%F koper-schulte-im-walde-2018-analogies
%X We present a computational model to detect and distinguish analogies in meaning shifts between German base and complex verbs. In contrast to corpus-based studies, a novel dataset demonstrates that “regular” shifts represent the smallest class. Classification experiments relying on a standard similarity model successfully distinguish between four types of shifts, with verb classes boosting the performance, and affective features for abstractness, emotion and sentiment representing the most salient indicators.
%R 10.18653/v1/N18-2024
%U https://aclanthology.org/N18-2024
%U https://doi.org/10.18653/v1/N18-2024
%P 150-156
Markdown (Informal)
[Analogies in Complex Verb Meaning Shifts: the Effect of Affect in Semantic Similarity Models](https://aclanthology.org/N18-2024) (Köper & Schulte im Walde, NAACL 2018)
ACL