@inproceedings{sung-etal-2020-clac,
title = "{CL}a{C} at {S}em{E}val-2020 Task 5: Muli-task Stacked {B}i-{LSTM}s",
author = "Sung, MinGyou and
Bagherzadeh, Parsa and
Bergler, Sabine",
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-1.54",
doi = "10.18653/v1/2020.semeval-1.54",
pages = "445--450",
abstract = "We consider detection of the span of antecedents and consequents in argumentative prose a structural, grammatical task. Our system comprises a set of stacked Bi-LSTMs trained on two complementary linguistic annotations. We explore the effectiveness of grammatical features (POS and clause type) through ablation. The reported experiments suggest that a multi-task learning approach using this external, grammatical knowledge is useful for detecting the extent of antecedents and consequents and performs nearly as well without the use of word embeddings.",
}
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<abstract>We consider detection of the span of antecedents and consequents in argumentative prose a structural, grammatical task. Our system comprises a set of stacked Bi-LSTMs trained on two complementary linguistic annotations. We explore the effectiveness of grammatical features (POS and clause type) through ablation. The reported experiments suggest that a multi-task learning approach using this external, grammatical knowledge is useful for detecting the extent of antecedents and consequents and performs nearly as well without the use of word embeddings.</abstract>
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%0 Conference Proceedings
%T CLaC at SemEval-2020 Task 5: Muli-task Stacked Bi-LSTMs
%A Sung, MinGyou
%A Bagherzadeh, Parsa
%A Bergler, Sabine
%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 sung-etal-2020-clac
%X We consider detection of the span of antecedents and consequents in argumentative prose a structural, grammatical task. Our system comprises a set of stacked Bi-LSTMs trained on two complementary linguistic annotations. We explore the effectiveness of grammatical features (POS and clause type) through ablation. The reported experiments suggest that a multi-task learning approach using this external, grammatical knowledge is useful for detecting the extent of antecedents and consequents and performs nearly as well without the use of word embeddings.
%R 10.18653/v1/2020.semeval-1.54
%U https://aclanthology.org/2020.semeval-1.54
%U https://doi.org/10.18653/v1/2020.semeval-1.54
%P 445-450
Markdown (Informal)
[CLaC at SemEval-2020 Task 5: Muli-task Stacked Bi-LSTMs](https://aclanthology.org/2020.semeval-1.54) (Sung et al., SemEval 2020)
ACL