17 research outputs found
Data-driven identification of fixed expressions and their modifiability
This thesis originated from the need for a description of the
linguistic behavior of Dutch fixed expressions in a
computational model. This work addresses the following
problems: (i) which criteria determine that an expression in
language use has to be described as a fixed expression,
(ii) how (automatic) identification models can capture such
criteria and (iii) how to predict whether such expressions allow
variation and modification.
The properties and the behavior of fixed expressions are still
poorly understood. The type and number of irregularities vary
across expressions.
The author argues that the idiosyncratic behavior affecting one
or more levels of linguistic analysis suffices to establish that
an expression qualifies as a fixed expression.
To identify fixed expressions, Villada Moirón proposes the use of
hybrid models that combine statistics and linguistic nowledge.
In order to be successful, the identification models need to
capture irregularities that affect the morphology,
syntactic distribution and meaning, in addition
to the lexical associations between the word components.
To establish the potential for variation and modification, a
corpus-based method extracts relevant evidence
from anannotated corpus.
The evidence allows us distinguish various
types of support verb constructions. Villada Moiron observes
that the presence of certain determiner changes correlate
with a potential for modification, albeit less than perfectly.
The methods need to be tested further with other types of fixed
expressions but it seems that their design features are
appropriate for the task. Such methods are crucial to improve
the description of fixed expressions in lexical and computational
resources.