Semiring frameworks and algorithms for shortest-distance problems
Journal of Automata, Languages and Combinatorics
Learn - Filter - Apply - Forget. Mixed Approaches to Named Entity Recognition
NLDB'01 Proceedings of the 6th International Workshop on Applications of Natural Language to Information Systems
ACL '95 Proceedings of the 33rd annual meeting on Association for Computational Linguistics
Finite-state parsing and disambiguation
COLING '90 Proceedings of the 13th conference on Computational linguistics - Volume 2
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This paper presents a new approach to proper noun recognition and classification in which the knowledge of ambiguities within morphological analyses is used exhaustively in the analysis. Here a proper noun recognizer/classifier is defined by proper noun context patterns on the one hand and by a filter that takes the ambiguity information into account on the other hand. Furthermore, techniques like a lemma based coreference resolution or the softening of the closed world assumption made by the morphology are presented which improve the analysis. The approach is implemented by weighted finite state transducers and tested within the analysis system SynCoP via a hand-written grammar.