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1
Automated text simplification as a preprocessing step for machine translation into an under-resourced language
In: Štajner, Sanja orcid:0000-0002-7780-7035 and Popović, Maja orcid:0000-0001-8234-8745 (2019) Automated text simplification as a preprocessing step for machine translation into an under-resourced language. In: Recent Advances in Natural Language Processing (RANLP 2019), 2-4 Sept 2019, Varna, Bulgaria. (2019)
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2
Are ambiguous conjunctions problematic for machine translation?
In: Popović, Maja orcid:0000-0001-8234-8745 and Castilho, Sheila orcid:0000-0002-8416-6555 (2019) Are ambiguous conjunctions problematic for machine translation? In: Recent Advances in Natural Language Processing (RANLP 2019), 2 - 4 Sept 2019, Varna, Bulgaria. (2019)
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3
Natural Language Generation
In: Handbook of Computational Linguistics (2nd edition) ; https://hal.archives-ouvertes.fr/hal-02079245 ; Mitkov, Ruslan. Handbook of Computational Linguistics (2nd edition), In press (2019)
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4
Bridging the Gap: Attending to Discontinuity in Identification of Multiword Expressions ...
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5
Summary Refinement through Denoising
In: Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2019) (2019)
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6
Large-Scale Hierarchical Alignment for Data-driven Text Rewriting
In: Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2019) (2019)
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7
Do Online Resources Give Satisfactory Answers to Questions about Meaning and Phraseology?
Hanks, Patrick; Franklin, Emma. - : Springer, 2019
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8
RGCL at IDAT: deep learning models for irony detection in Arabic language
In: 2517 ; 416 ; 425 (2019)
Abstract: This article describes the system submitted by the RGCL team to the IDAT 2019 Shared Task: Irony Detection in Arabic Tweets. The system detects irony in Arabic tweets using deep learning. The paper evaluates the performance of several deep learning models, as well as how text cleaning and text pre-processing influence the accuracy of the system. Several runs were submitted. The highest F1 score achieved for one of the submissions was 0.818 making the team RGCL rank 4th out of 10 teams in final results. Overall, we present a system that uses minimal pre-processing but capable of achieving competitive results.
Keyword: Computational linguistics; Irony Detection
URL: http://hdl.handle.net/2436/622828
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9
Bridging the gap: attending to discontinuity in identification of multiword expressions
Mitkov, Ruslan; Kouchaki, Samaneh; Taslimipoor, Shiva. - : Association for Computational Linguistics, 2019
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10
RGCL-WLV at SemEval-2019 Task 12: Toponym Detection
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11
SenZi: A sentiment analysis lexicon for the latinised Arabic (Arabizi)
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