Archive:Brill tagger

2006-01-09T20:54:54Z

80.129.123.125: Link to "part-of-speech tagging" article

The '''Brill Tagger''' is a method for doing [[part-of-speech tagging]]. It was exposed by [[Eric Brill]] in his 1993 PhD thesis [http://www.cs.jhu.edu/~brill/dissertation.ps]. It can be summarised as an "error-driven transformation-based tagger". It is
*error-driven in the sense that is recourses to supervised learning
* transformation-based in the sense that a tag is assigned to each word and changed using a set of predefined rules. Note: If the word is known, it first assigns the most frequent tag, or if the word is unknown, it naively assigns the tag "noun" to it. Applying over and over these rules, changing the incorrect tags, a quite high accuracy is achieved.

== Algorithm ==
The algorithm goes as follow:
* Initialisation:
** Known words (in vocabulary): assigning the most frequent tag associated to a form of the word
** Unknown words (out of vocabulary) :
*** Proper noun if capitalised and simple noun else (1992)
*** Learning or guessing rules on the same basis as [[contextual rules]] (1994)
* Learning Phase
** Iteratively compute the error score of each candidate rule (difference between the number of errors before and after applying the rule)
** Select the best (higher score) rule.
** Add it to the rule set and apply it to the text.
** Repeat until no rule has a score above a given threshold (that is, until applying new rules leaves the text in the same state, which is then supposed to be the final state of the tagging).

== Rules ==
Lexical rules are used for the initialisation, and contextual rules are used to correct the tags.
*Lexical rules: ''word'' → ''tag'' IF ''Condition'' (example: identification of [[suffix]]es like "-tion")
*Contextual rules: ''tag1'' → ''tag2'' IF ''Condition'' (example: "preceding/following tag is ''X''", "preceding/following word is ''w''")

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