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able to predict the occurrence of the benefactive construction with high accuracy. Taking Bresnan
‟s 2007 argument into account, that having no access to the intuition of the language speakers, the regression models allow us to notice the
dynamics of syntactic alternation and to predict the alternation in a cognitively realistic way.
Finally, the research was limited to the analysis of the shared significant features toward dative and benefactive constructions. When the shared features
were obtained, the cross-model application was done to check the interchangeability of the two probabilistic models. This method provided the
information of the different effect sizes of the features when applied to dative and to benefactive. By providing the different size of the effect and testing the models
into the cross-data sets of dative and benefactive, the research was able to explain whether dative and benefactive alternations were very much similar or not.
1.3 Research Questions
The research intends to answer the following formulated problems: 1. What linguistic features affect the choice of benefactive construction?
2. How do the significant features differ in the effect size on ditransitive construction?
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1.4 Research Objectives
As stated previously, the research has been conducted to answer the research questions above. There are two objectives that the research tries to
overcome. The first objective of this research is to reveal the features which are significant to the choice of benefactice construction. Analyzing the features
relevant to the choice of benefactive construction will help in understanding the natural use of this construction. As acquiring such a complicated pattern is
troublesome for the language users, for non-native speakers moreover, the research will help the language users to realize the construction in a cognitively
realistic way. Some features which are found significant to the choice of benefactive construction will be accommodating to predict the choice of
benefactive construction. The second research objective of this study is to identify the shared
relevant features of dative and benefactive construction and how they differ to each other. The corpus probabilistic models obtained from logistic regression
models are employed to find the direction and size of the feature effects. Hence, the cross-model application is done to check the possibility of model
interchangeability. To support the significant features toward benefactive construction, logit
formula of probabilistic benefactive construction is used in the predicting probabilities process. The logit model is used to predict the outcomes of instances
possessing some significant features toward benefactive construction. This logit formula provides the highly accurate prediction of the benefactive PP and double
object realizations. The idea of probabilistic grammar has been applied in some
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studies Bybee Hooper 2001; Bod
et al.
2003; Gahl Garnsey 2006; Gahl Yu 2006.
The mixed-effect of binary logistic model is combined with simple binary logistic model to bring about strong analysis of the feature relevance. The mix-
effect binary logistic model basically analyzes a single dependent variable based on many independent variables as predictors which are bounded in the equation.
The mix-effect binary logistic model occupies a dependent variable which is the ditransitivity of occurrence and 14 independent variables as predictors which are
the linguistic features affecting the ditransitivity. The mixed-effect binary logistic model will provide the effect of variables in the equation, and the simple binary
logistic model will give the effect of variables when are not in the equation. The effect of variables in the equation are needed to formulate the logit probabilistic
model, while the effect sizes from variables not in the equation are needed to show how each feature contribute to increase the model fit accuracy.
Complementing mixed-effect binary logistic model with simple binary logistic model, thus will offer the more precise and complete analysis of the significant
features toward dative and benefactive construction.
1.5 Research Benefits
