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A tagger is a device which assigns symbolic labels (tags) to linguistics units. The labels are taken from a predefined set of symbols (the so-called tag-set).


In most cases, a tagger assigns tags representing morpho-syntactic information to single word-forms or tokens. But there are also taggers which have been designed to identify semantic roles of noun phrases or prepositional phrases (sense tagging), and sometimes identifying the structure of a text is considered as a kind of tagging (discourse structure tagging).

Conceptually, tagging can be considered as a three step process: (i). identification of the relevant units (ii). assigning all possible labels (e.g. by lexical look-up, applying heuristics, etc.) (iii). disambiguation.

It is common practice to distinguish between rule-based and stochastic taggers, though some taggers combine rules and stochastic information.

In general, state-of-the-art taggers achieve a precision of at least 95% for morpho-syntactic tagging.


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