@inproceedings{gari-soler-apidianaki-2020-bert,
title = "{BERT} Knows {P}unta {C}ana is not just beautiful, it{'}s gorgeous: Ranking Scalar Adjectives with Contextualised Representations",
author = "Gar{\'\i} Soler, Aina and
Apidianaki, Marianna",
editor = "Webber, Bonnie and
Cohn, Trevor and
He, Yulan and
Liu, Yang",
booktitle = "Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)",
month = nov,
year = "2020",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2020.emnlp-main.598",
doi = "10.18653/v1/2020.emnlp-main.598",
pages = "7371--7385",
abstract = "Adjectives like pretty, beautiful and gorgeous describe positive properties of the nouns they modify but with different intensity. These differences are important for natural language understanding and reasoning. We propose a novel BERT-based approach to intensity detection for scalar adjectives. We model intensity by vectors directly derived from contextualised representations and show they can successfully rank scalar adjectives. We evaluate our models both intrinsically, on gold standard datasets, and on an Indirect Question Answering task. Our results demonstrate that BERT encodes rich knowledge about the semantics of scalar adjectives, and is able to provide better quality intensity rankings than static embeddings and previous models with access to dedicated resources.",
}
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%0 Conference Proceedings
%T BERT Knows Punta Cana is not just beautiful, it’s gorgeous: Ranking Scalar Adjectives with Contextualised Representations
%A Garí Soler, Aina
%A Apidianaki, Marianna
%Y Webber, Bonnie
%Y Cohn, Trevor
%Y He, Yulan
%Y Liu, Yang
%S Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)
%D 2020
%8 November
%I Association for Computational Linguistics
%C Online
%F gari-soler-apidianaki-2020-bert
%X Adjectives like pretty, beautiful and gorgeous describe positive properties of the nouns they modify but with different intensity. These differences are important for natural language understanding and reasoning. We propose a novel BERT-based approach to intensity detection for scalar adjectives. We model intensity by vectors directly derived from contextualised representations and show they can successfully rank scalar adjectives. We evaluate our models both intrinsically, on gold standard datasets, and on an Indirect Question Answering task. Our results demonstrate that BERT encodes rich knowledge about the semantics of scalar adjectives, and is able to provide better quality intensity rankings than static embeddings and previous models with access to dedicated resources.
%R 10.18653/v1/2020.emnlp-main.598
%U https://aclanthology.org/2020.emnlp-main.598
%U https://doi.org/10.18653/v1/2020.emnlp-main.598
%P 7371-7385
Markdown (Informal)
[BERT Knows Punta Cana is not just beautiful, it’s gorgeous: Ranking Scalar Adjectives with Contextualised Representations](https://aclanthology.org/2020.emnlp-main.598) (Garí Soler & Apidianaki, EMNLP 2020)
ACL