Abstract
In this paper, we present a robust incremental architecture for natural language processing centered around syntactic analysis but allowing at the same time the description of specialized modules, like named entity recognition. We show that the flexibility of our approach allows us to intertwine general and specific processing, which has a mutual improvement effect on their respective results: for example, syntactic analysis clearly benefits from named entity recognition as a pre-processing step, but named entity recognition can also take advantage of deep syntactic information.
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Brun, C., Hagège, C. (2004). Intertwining Deep Syntactic Processing and Named Entity Detection. In: Vicedo, J.L., Martínez-Barco, P., Muńoz, R., Saiz Noeda, M. (eds) Advances in Natural Language Processing. EsTAL 2004. Lecture Notes in Computer Science(), vol 3230. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30228-5_18
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DOI: https://doi.org/10.1007/978-3-540-30228-5_18
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