  The dissertation addresses the design of parsing grammars for automatic
surface-syntactic analysis of unconstrained English text. It consists of a
summary and three articles. {\it Morphological disambiguation} documents a
grammar for morphological (or part-of-speech) disambiguation of English, done
within the Constraint Grammar framework proposed by Fred Karlsson. The
disambiguator seeks to discard those of the alternative morphological analyses
proposed by the lexical analyser that are contextually illegitimate. The 1,100
constraints express some 23 general, essentially syntactic statements as
restrictions on the linear order of morphological tags. The error rate of the
morphological disambiguator is about ten times smaller than that of another
state-of-the-art probabilistic disambiguator, given that both are allowed to
leave some of the hardest ambiguities unresolved. This accuracy suggests the
viability of the grammar-based approach to natural language parsing, thus also
contributing to the more general debate concerning the viability of
probabilistic vs.\ linguistic techniques. {\it Experiments with heuristics}
addresses the question of how to resolve those ambiguities that survive the
morphological disambiguator. Two approaches are presented and empirically
evaluated: (i) heuristic disambiguation constraints and (ii) techniques for
learning from the fully disambiguated part of the corpus and then applying this
information to resolving remaining ambiguities.
