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Minimal Commitment and Full Lexical Disambiguation: Balancing Rules and Hidden Markov Models

In this paper we describe the construction of a part-of-speech tagger both for medical document retrieval purposes and XP extraction. Therefore we have designed a double system: for retrieval purposes, we rely on a rule-based architecture, called minimal commitment, which is likely to be completed by a data-driven tool (HMM) when full disambiguation is necessary.