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SRL4ORL: Improving Opinion Role Labeling using Multi-task Learning with Semantic Role Labeling
[article]
2018
arXiv
pre-print
Preserved Fulltext
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We suspect this is due to the scarcity of labeled training data and address this issue using different multi-task learning (MTL) techniques with a related task which has substantially more data, i.e. ...
Semantic Role Labeling (SRL). We show that two MTL models improve significantly over the single-task model for labeling of both holders and targets, on the development and the test sets. ...
Conclusions We address the problem of scarcity of annotated training data for labeling of opinion holders and targets (ORL) using multi-task learning (MTL) with Semantic Role Labeling (SRL). ...
arXiv:1711.00768v3
fatcat:mi7vca5xnzerpl7xdhvyuxa5ra
SRL4ORL: Improving Opinion Role Labeling Using Multi-Task Learning with Semantic Role Labeling
2018
Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers)
Preserved Fulltext
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We suspect this is due to the scarcity of labeled training data and address this issue using different multi-task learning (MTL) techniques with a related task which has substantially more data, i.e. ...
Semantic Role Labeling (SRL). We show that two MTL models improve significantly over the single-task model for labeling of both holders and targets, on the development and the test sets. ...
Conclusions We address the problem of scarcity of annotated training data for labeling of opinion holders and targets (ORL) using multi-task learning (MTL) with Semantic Role Labeling (SRL). ...
doi:10.18653/v1/n18-1054
dblp:conf/naacl/MarasovicF18
fatcat:leo5fmomd5dybknly2lk4tfjcq
Enhancing Opinion Role Labeling with Semantic-Aware Word Representations from Semantic Role Labeling
2019
Proceedings of the 2019 Conference of the North
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The task is highly correlative with semantic role labeling (SRL), which identifies important semantic arguments such as agent and patient for a given predicate. ...
Opinion role labeling (ORL) is an important task for fine-grained opinion mining, which identifies important opinion arguments such as holder and target for a given opinion trigger. ...
The focused task behaves very similar with semantic role labeling (SRL) which identifies the core semantic roles for given predicates. ...
doi:10.18653/v1/n19-1066
dblp:conf/naacl/ZhangLF19
fatcat:fnxvitembngkxpfuu5khhkt73e
SKEP: Sentiment Knowledge Enhanced Pre-training for Sentiment Analysis
[article]
2020
arXiv
pre-print
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In particular, the prediction of aspect-sentiment pairs is converted into multi-label classification, aiming to capture the dependency between words in a pair. ...
In this paper, we introduce Sentiment Knowledge Enhanced Pre-training (SKEP) in order to learn a unified sentiment representation for multiple sentiment analysis tasks. ...
, and opinion role labeling. ...
arXiv:2005.05635v2
fatcat:4dutgfb32naeviokmuikwdzcyu
SGPT: Semantic Graphs based Pre-training for Aspect-based Sentiment Analysis
[article]
2021
arXiv
pre-print
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/sentiment terms.We then optimize the pre-trained language model with the semantic graphs.Empirical studies on several downstream tasks show that proposed model outperforms strong pre-trained baselines ...
semantic graphs for sentiment analysis.In particular, we introduce Semantic Graphs based Pre-training(SGPT) using semantic graphs to obtain synonym knowledge for aspect-sentiment pairs and similar aspect ...
and aspect-sentiment pair prediction and aspect-sentiment pairs is converted into multi-label classification. ...
arXiv:2105.12305v1
fatcat:f7nyyzeeirbfvch3y5crmb2w2a
Chinese Opinion Role Labeling with Corpus Translation: A Pivot Study
2021
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
unpublished
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Cross-lingual transfer Improving opinion role labeling using multi-task
learning for pos tagging without cross-lingual re- learning with semantic role labeling. ...
Srl4orl: Im-
(Volume 1: Long Papers), pages 919–929, Berlin, proving opinion role labeling using multi-task learn-
Germany. ...
doi:10.18653/v1/2021.emnlp-main.796
fatcat:43lnnqgvmnagrlwl2367jjpn4a
SKEP: Sentiment Knowledge Enhanced Pre-training for Sentiment Analysis
2020
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
unpublished
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A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
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In particular, the prediction of aspect-sentiment pairs is converted into multi-label classification, aiming to capture the dependency between words in a pair. ...
In this paper, we introduce Sentiment Knowledge Enhanced Pre-training (SKEP) in order to learn a unified sentiment representation for multiple sentiment analysis tasks. ...
, and opinion role labeling. ...
doi:10.18653/v1/2020.acl-main.374
fatcat:bbzkwvw6zzdp7hfslgsu7jyovm