Abstract
In these days, we are witnessing a growing trend of exploiting lightweight linguistic analysis for converting of the vast amount of raw textual data into structured knowledge. Although a considerable number of monolingual and task-oriented NLP systems have been presented, relatively few general-purpose architectures exist, e.g., GATE [1] or ELLOGON [2].
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Drożdżyński, W., Krieger, HU., Piskorski, J., Schäfer, U. (2006). SProUT – A General-Purpose NLP Framework Integrating Finite-State and Unification-Based Grammar Formalisms. In: Yli-Jyrä, A., Karttunen, L., Karhumäki, J. (eds) Finite-State Methods and Natural Language Processing. FSMNLP 2005. Lecture Notes in Computer Science(), vol 4002. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11780885_35
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DOI: https://doi.org/10.1007/11780885_35
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