Abstract
The requirements of different NLP applications have strong implications on the design and implementation of the related syntactic recognisers. In this paper, a fine-grained modular parser design framework is presented. Our aim is to reduce the design of a parsing processors to the composition of a pool of basic modules. Results over sample parsers and criteria for optimising coverage and accuracy are discussed.
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Basili, R., Pazienza, M.T., Zanzotto, F.M. (2001). Flexible Parsing Architectures for NLP Applications. In: Esposito, F. (eds) AI*IA 2001: Advances in Artificial Intelligence. AI*IA 2001. Lecture Notes in Computer Science(), vol 2175. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45411-X_31
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DOI: https://doi.org/10.1007/3-540-45411-X_31
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