Multiobjective Genetic Programming for Natural Language Parsing and Tagging.
Lourdes Araujo.
Proc. Int. Conf. on Parallel Problem Solving from Nature, (PPSN VII)
LNCS 4193, pp. 302-311, Springer-Verlag (2006).

Parsing and Tagging are very important tasks in Natural Language Processing. Parsing amounts
to searching the correct combination of grammatical rules among those compatible with a given
sentence. Tagging amounts to labeling each word in a sentence with its lexical category and,
because many words belong to more than one lexical class, it turns out to be a disambiguation
task. Because parsing and tagging are related tasks, its simultaneous resolution can improve the
results of both of them. This work aims developing a multiobjective genetic program to perform
simultaneously statistical parsing and tagging. It combines the statistical data about grammar
rules and about tag sequences to guide the search of the best structure. Results show that any
of the implemented multiobjective optimization models improve on the results obtained in the
resolution of each problem separately.