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SRL4ORL: Improving Opinion Role Labeling using Multi-task Learning with Semantic Role Labeling [article]

Ana Marasović, Anette Frank
2018 arXiv   pre-print
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

Ana Marasović, Anette Frank
2018 Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers)  
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

Meishan Zhang, Peili Liang, Guohong Fu
2019 Proceedings of the 2019 Conference of the North  
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]

Hao Tian, Can Gao, Xinyan Xiao, Hao Liu, Bolei He, Hua Wu, Haifeng Wang, Feng Wu
2020 arXiv   pre-print
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]

Yong Qian, Zhongqing Wang, Rong Xiao, Chen Chen, Haihong Tang
2021 arXiv   pre-print
/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

Ranran Zhen, Rui Wang, Guohong Fu, Chengguo Lv, Meishan Zhang
2021 Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing   unpublished
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

Hao Tian, Can Gao, Xinyan Xiao, Hao Liu, Bolei He, Hua Wu, Haifeng Wang, feng wu
2020 Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics   unpublished
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