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Cross-lingual Semantic Role Labeling with Model Transfer
[article]
2020
arXiv
pre-print
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Prior studies show that cross-lingual semantic role labeling (SRL) can be achieved by model transfer under the help of universal features. ...
In this paper, we fill the gap of cross-lingual SRL by proposing an end-to-end SRL model that incorporates a variety of universal features and transfer methods. ...
Semantic Role Labeling A line of research efforts has been made for semantic role labeling. ...
arXiv:2008.10284v1
fatcat:v3zwcyw22faz3ifofq5mrh2gpu
Global Methods for Cross-lingual Semantic Role and Predicate Labelling
2014
International Conference on Computational Linguistics
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We build two global models, one for predicate labelling and one for role labelling, each tailored to the task at hand. ...
We address the problem of transferring semantic annotations to new languages using parallel corpora. ...
The ideas behind their cross-lingual model adaptation resemble the ideas behind our global method for semantic role labelling. ...
dblp:conf/coling/PlasAC14
fatcat:3xtkrjlmifchfgc3ojya7y4tti
Scaling up Automatic Cross-Lingual Semantic Role Annotation
2011
Annual Meeting of the Association for Computational Linguistics
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Previous approaches to cross-lingual transfer of semantic annotations have addressed this problem with encouraging results on a small scale. ...
Moreover, we improve the quality of the transferred semantic annotations by using a joint syntacticsemantic parser that learns the correlations between syntax and semantics of the target language and smooths ...
Johansson and Nugues (2006) trained a FrameNet-based semantic role labeller for Swedish on annotations transferred cross-lingually from English parallel data. ...
dblp:conf/acl/PlasMH11
fatcat:ednh5b7yf5cdddg6guyqtzbzaa
Cross-Lingual Semantic Role Labeling with High-Quality Translated Training Corpus
[article]
2020
arXiv
pre-print
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Cross-lingual SRL is one promising way to address the problem, which has achieved great advances with the help of model transferring and annotation projection. ...
Many efforts of research are devoted to semantic role labeling (SRL) which is crucial for natural language understanding. ...
Table 2 : 2 Results of cross-lingual transfer from English.
Table 3 : 3 Cross-lingual transfer with multiple sources. ...
arXiv:2004.06295v2
fatcat:bo2b3c2asjhjpf3xbam74qpejm
Cross-Lingual SRL Based upon Universal Dependencies
2017
RANLP 2017 - Recent Advances in Natural Language Processing Meet Deep Learning
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In this paper, we introduce a cross-lingual Semantic Role Labeling (SRL) system with language independent features based upon Universal Dependencies. ...
Our SRL system is based upon cross-lingual features derived from universal dependency trees and supervised learning that utilizes a maximum entropy classifier. ...
The results of the cross-lingual experiment measured by the unsupervised metrics (Table 4 -F c 1 row) indicate that the transfer of semantic roles from English to all other languages is possible. ...
doi:10.26615/978-954-452-049-6_077
dblp:conf/ranlp/PrazakK17
fatcat:wgwkrvsysjetjldcm4fve2col4
WikiBank: Using Wikidata to Improve Multilingual Frame-Semantic Parsing
2020
International Conference on Language Resources and Evaluation
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We also integrate this form of supervision into an off-the-shelf frame-semantic parser and allow cross-lingual transfer. ...
for semantic parsers. ...
Furthermore, we experiment with reducing the full label sets in the corpora to a common, simplified label set, to facilitate cross-lingual transfer. ...
dblp:conf/lrec/SasBS20
fatcat:dvaaatbtdfdbffggczeydv3vz4
CLAR: A Cross-Lingual Argument Regularizer for Semantic Role Labeling
[article]
2020
arXiv
pre-print
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Semantic role labeling (SRL) identifies predicate-argument structure(s) in a given sentence. ...
To leverage such similarity in annotation space across languages, we propose a method called Cross-Lingual Argument Regularizer (CLAR). ...
Cross-Lingual Transfer from Target to Source Language: Interestingly, cross-lingual transfer by CLAR also helps improving the performance of languages with abundant training data. ...
arXiv:2011.04732v1
fatcat:hrop2bxfhjephm5ojb6zfudphq
Cross-lingual Structure Transfer for Relation and Event Extraction
2019
Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)
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The event argument role labeling model transferred from English to Chinese achieves similar performance as the model trained from Chinese. ...
Extensive experiments on cross-lingual relation and event transfer among English, Chinese, and Arabic demonstrate that our approach achieves performance comparable to state-of-the-art supervised models ...
Cross-
lingual transfer of semantic role labeling models. In
Proceedings of the 51st Annual Meeting of the Asso-
ciation for Computational Linguistics. ...
doi:10.18653/v1/d19-1030
dblp:conf/emnlp/SubburathinamLJ19
fatcat:3vwt72efyrfn7ojd6pkn64q7w4
Translate and Label! An Encoder-Decoder Approach for Cross-lingual Semantic Role Labeling
[article]
2019
arXiv
pre-print
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We propose a Cross-lingual Encoder-Decoder model that simultaneously translates and generates sentences with Semantic Role Labeling annotations in a resource-poor target language. ...
We then train our model in a cross-lingual setting to generate new SRL labeled data. ...
We are grateful to our annotators and tó Eva Mújdricza-Maydt for her assistance with the human evaluation setup. ...
arXiv:1908.11326v1
fatcat:uequw67mdnernipvnn7hd3xvv4
Translate and Label! An Encoder-Decoder Approach for Cross-lingual Semantic Role Labeling
2019
Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)
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We propose a Cross-lingual Encoder-Decoder model that simultaneously translates and generates sentences with Semantic Role Labeling annotations in a resource-poor target language. ...
We then train our model in a cross-lingual setting to generate new SRL labeled data. ...
We are grateful to our annotators and tó Eva Mújdricza-Maydt for her assistance with the human evaluation setup. ...
doi:10.18653/v1/d19-1056
dblp:conf/emnlp/DazaF19
fatcat:c2w2hf2ahjayfd6ng4cwblxd4a
Weakly Supervised Cross-lingual Semantic Relation Classification via Knowledge Distillation
2019
Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)
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We introduce a cross-lingual relation classifier trained only with English examples and a bilingual dictionary. ...
On new English-Chinese and English-Hindi test sets, the resulting models largely outperform baselines that more naïvely rely on bilingual embeddings or dictionaries for cross-lingual transfer, and approach ...
Our approach transfers knowledge from a monolingual teacher model to a cross-lingual student model. ...
doi:10.18653/v1/d19-1532
dblp:conf/emnlp/VyasC19
fatcat:fvvosxraxfd6hhideptggeo66i
Cross-lingual Structure Transfer for Zero-resource Event Extraction
2020
International Conference on Language Resources and Evaluation
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Most current cross-lingual transfer learning methods for Information Extraction (IE) have been applied to local sequence labeling tasks. ...
To tackle more complex tasks such as event extraction, we need to transfer graph structures (event trigger linked to multiple arguments with various roles) across languages. ...
Figure 2 : 2 Figure 2: Overall Framework for Cross-lingual Event Structure Transfer.
Figure 3 : 3 Figure 3: Comparison with Learning Curves for Supervised Bi-LSTM models on trigger labeling. ...
dblp:conf/lrec/LuSJMCSV20
fatcat:nebmjihr2zhkxk7ullz4c33woq
A Knowledge-Enhanced Adversarial Model for Cross-lingual Structured Sentiment Analysis
[article]
2022
arXiv
pre-print
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Notably, we propose a Knowledge-Enhanced Adversarial Model () with both implicit distributed and explicit structural knowledge to enhance the cross-lingual transfer. ...
In this paper, we focus on the cross-lingual structured sentiment analysis task, which aims to transfer the knowledge from the source language to the target one. ...
[13] applied multi-lingual contextualized word embedding for crosslingual tasks, such as semantic role labeling, dependency parsing and named entity recognition. ...
arXiv:2205.15514v1
fatcat:6hqs2ok5qrfmdmnrkusqtaesya
Cross-lingual Model Transfer Using Feature Representation Projection
2014
Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)
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This approach displays competitive performance on model transfer for semantic role labeling when compared to direct model transfer and annotation projection and suggests interesting directions for further ...
We propose a novel approach to crosslingual model transfer based on feature representation projection. ...
by cross-lingual transfer. ...
doi:10.3115/v1/p14-2095
dblp:conf/acl/KozhevnikovT14
fatcat:ufmyu2ay65ee5lctwwje3lppqy
Zero-shot Cross-lingual Conversational Semantic Role Labeling
[article]
2022
arXiv
pre-print
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While conversational semantic role labeling (CSRL) has shown its usefulness on Chinese conversational tasks, it is still under-explored in non-Chinese languages due to the lack of multilingual CSRL annotations ...
Our model implicitly learns language-agnostic, conversational structure-aware and semantically rich representations with the hierarchical encoders and elaborately designed pre-training objectives. ...
To our best knowledge, our work is the first step to cross-lingual CSRL. Conversational semantic role labeling. ...
arXiv:2204.04914v1
fatcat:bhniez3z6zgvliankwmit2hwji
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