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On the Evolution of Syntactic Information Encoded by BERT's Contextualized Representations ...
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How much pretraining data do language models need to learn syntax? ...
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Assessing the Syntactic Capabilities of Transformer-based Multilingual Language Models ...
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Assessing the Syntactic Capabilities of Transformer-based Multilingual Language Models ...
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Semantically-oriented text planning for automatic summarization
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In: TDX (Tesis Doctorals en Xarxa) (2021)
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The Third Multilingual Surface Realisation Shared Task (SR'20): Overview and Evaluation Results ...
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The Third Multilingual Surface Realisation Shared Task (SR'20): Overview and Evaluation Results ...
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CollFrEn: Rich Bilingual English--French Collocation Resource ...
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The second multilingual surface realisation shared task (SR'19): Overview and evaluation results
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In: Mille, Simon orcid:0000-0002-8852-2764 , Anja, Belz, Bohnet, Bernd, Graham, Yvette and Wanner, Leo orcid:0000-0002-9446-3748 (2019) The second multilingual surface realisation shared task (SR'19): Overview and evaluation results. In: 2nd Workshop on Multilingual Surface Realisation (MSR 2019), 3 Nov 2019, Hong Kong, China. (2019)
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Abstract:
We report results from the SR’19 Shared Task, the second edition of a multilingual surface realisation task organised as part of the EMNLP’19 Workshop on Multilingual Surface Realisation. As in SR’18, the shared task comprised two different tracks: (a) a Shallow Track where the inputs were full UD structures with word order information removed and tokens lemmatised; and (b) a Deep Track where additionally, functional words and morphological information were removed. The Shallow Track was offered in 11, and the Deep Track in three languages. Systems were evaluated (a) automatically, using a range of intrinsic metrics, and (b) by human judges in terms of readability and meaning similarity to a reference. This report presents the evaluation results, along with descriptions of the SR’19 tracks, data and evaluation methods, as well as brief summaries of the participating systems. For full descriptions of the participating systems, please see the separate system reports elsewhere in this volume.
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Keyword:
Machine translating
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URL: http://doras.dcu.ie/24159/
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Collocation classification with unsupervised relation vectors
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A Multimodal Analytics Platform for Journalists Analyzing Large-Scale, Heterogeneous Multilingual, and Multimedia Content
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In: Front Robot AI (2018)
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Towards Distributional Semantics-Based Classification of Collocations for Collocation Dictionaries
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In: International Journal of Lexicography 30 (2017) 2, 167-186
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IDS OBELEX meta
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Multilingual Surface Realization Using Universal Dependency Trees
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Feature engineering for author profiling and identification: on the relevance of syntax and discourse
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In: TDX (Tesis Doctorals en Xarxa) (2017)
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Processament automàtic de patents: un exercici de terminologia computacional
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In: Terminàlia; Núm. 16 : desembre 2017; p. 54-56 ; 2013-6692 (2017)
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Combining Acoustic and Linguistic Features in Phrase-Oriented Prosody Prediction ...
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Classification of Grammatical Collocation Errors in the Writings of Learners of Spanish ; Clasificación de errores gramaticales colocacionales en textos de estudiantes de español
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