@inproceedings{bao-etal-2020-will,
title = "{W}ill{\_}{G}o at {S}em{E}val-2020 Task 3: An Accurate Model for Predicting the (Graded) Effect of Context in Word Similarity Based on {BERT}",
author = "Bao, Wei and
Che, Hongshu and
Zhang, Jiandong",
editor = "Herbelot, Aurelie and
Zhu, Xiaodan and
Palmer, Alexis and
Schneider, Nathan and
May, Jonathan and
Shutova, Ekaterina",
booktitle = "Proceedings of the Fourteenth Workshop on Semantic Evaluation",
month = dec,
year = "2020",
address = "Barcelona (online)",
publisher = "International Committee for Computational Linguistics",
url = "https://aclanthology.org/2020.semeval-1.38",
doi = "10.18653/v1/2020.semeval-1.38",
pages = "301--306",
abstract = "Natural Language Processing (NLP) has been widely used in the semantic analysis in recent years. Our paper mainly discusses a methodology to analyze the effect that context has on human perception of similar words, which is the third task of SemEval 2020. We apply several methods in calculating the distance between two embedding vector generated by Bidirectional Encoder Representation from Transformer (BERT). Our team will go won the 1st place in Finnish language track of subtask1, the second place in English track of subtask1.",
}
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%0 Conference Proceedings
%T Will_Go at SemEval-2020 Task 3: An Accurate Model for Predicting the (Graded) Effect of Context in Word Similarity Based on BERT
%A Bao, Wei
%A Che, Hongshu
%A Zhang, Jiandong
%Y Herbelot, Aurelie
%Y Zhu, Xiaodan
%Y Palmer, Alexis
%Y Schneider, Nathan
%Y May, Jonathan
%Y Shutova, Ekaterina
%S Proceedings of the Fourteenth Workshop on Semantic Evaluation
%D 2020
%8 December
%I International Committee for Computational Linguistics
%C Barcelona (online)
%F bao-etal-2020-will
%X Natural Language Processing (NLP) has been widely used in the semantic analysis in recent years. Our paper mainly discusses a methodology to analyze the effect that context has on human perception of similar words, which is the third task of SemEval 2020. We apply several methods in calculating the distance between two embedding vector generated by Bidirectional Encoder Representation from Transformer (BERT). Our team will go won the 1st place in Finnish language track of subtask1, the second place in English track of subtask1.
%R 10.18653/v1/2020.semeval-1.38
%U https://aclanthology.org/2020.semeval-1.38
%U https://doi.org/10.18653/v1/2020.semeval-1.38
%P 301-306
Markdown (Informal)
[Will_Go at SemEval-2020 Task 3: An Accurate Model for Predicting the (Graded) Effect of Context in Word Similarity Based on BERT](https://aclanthology.org/2020.semeval-1.38) (Bao et al., SemEval 2020)
ACL