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SProUT – A General-Purpose NLP Framework Integrating Finite-State and Unification-Based Grammar Formalisms

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Finite-State Methods and Natural Language Processing (FSMNLP 2005)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4002))

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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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References

  1. Bontcheva, K., Tablan, V., Maynard, D., Cunningham, H.: Evolving GATE to Meet New Challenges in Language Engineering. Natural Language Engineering 12(3/4), 349–373 (2004)

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  3. Drożdżyński, W., Krieger, H.-U., Piskorski, J., Schäfer, U.: Shallow Processing with Unification and Typed Feature Structures – Foundations and Applications. Künstliche Intelligenz 1/04, 17–23 (2004)

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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

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-35467-3

  • Online ISBN: 978-3-540-35469-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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