[PDF] Lemmatization for variation-rich languages using deep learning | Semantic Scholar Skip to search formSkip to main content> Semantic Scholar's Logo Search Sign InCreate Free Account You are currently offline. Some features of the site may not work correctly. DOI:10.1093/llc/fqw034 Corpus ID: 30890330Lemmatization for variation-rich languages using deep learning @article{Kestemont2017LemmatizationFV, title={Lemmatization for variation-rich languages using deep learning}, author={M. Kestemont and G. D. Pauw and R. V. Nie and W. Daelemans}, journal={Digit. Scholarsh. Humanit.}, year={2017}, volume={32}, pages={797-815} } M. Kestemont, G. D. Pauw, +1 author W. Daelemans Published 2017 Computer Science Digit. Scholarsh. Humanit. In this article, we describe a novel approach to sequence tagging for languages that are rich in (e.g. orthographic) surface variation. We focus on lemmatization, a basic step in many processing pipelines in the Digital Humanities. While this task has long been considered solved for modern languages such as English, there exist many (e.g. historic) languages for which the problem is harder to solve, due to a lack of resources and unstable orthography. Our approach is based on recent advances in… Expand View via Publisher clips.uantwerpen.be Save to Library Create Alert Cite Launch Research Feed Share This Paper 11 CitationsHighly Influential Citations 1 Background Citations 4 Methods Citations 2 View All Figures, Tables, and Topics from this paper table 1 figure 1 figure 2 table 3 figure 3 table 4 table 5 table 6 table 7 table 8 table 9 View All 11 Figures & Tables Lemmatisation Deep learning Convolution Feature learning Digital humanities Orthographic projection Existential quantification Control theory Artificial neural network Pipeline (computing) 11 Citations Citation Type Citation Type All Types Cites Results Cites Methods Cites Background Has PDF Publication Type Author More Filters More Filters Filters Sort by Relevance Sort by Most Influenced Papers Sort by Citation Count Sort by Recency Improving Lemmatization of Non-Standard Languages with Joint Learning Enrique Manjavacas, Ákos Kádár, M. 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