Two competing and largely incompatible classes of model dominate current sentence processing research. One is called Linear view. The best known account of this class is the garden-path model, in which the processor makes initial decisions on the basis of strategies defined in terms of syntactic information alone and uses thematic information (such as determined by minimal attachment and late closure).According to this class, the processor computes syntactic analyses serially, in two stages. In the first stage, it draws on a restricted range of information to construct an initial analysis. During the second stage, it accesses other sources of information, which may sometimes cause it to abandon its initial analysis and compute another. The second class of model assumes that the processor can activate multiple analyses in parallel. It employs both syntactic and nonsyntactic information in a single stage to foreground one analysis, but other analyses remain activated, which is called Parallel view or competing model. The best known account of this class is the constraint-based model. In the framework of the contingency model, which mechanism the subjects will explore to deal with the syntactic ambiguity corpus depends on the contingent properties of the ambiguity motivator. The so-called "ambiguity motivator" refers to the information point that promotes and forces people to make a choice between the alternative analysis. According to the contingent properties of the ambiguity motivator, there are three conditions in the resolution of syntactic ambiguity. In the first case, the ambiguity motivator does not appear in any position of the corpus. In this case, the individual will generate an analysis based on their syntactic knowledge, context and their preference and so on. They won’t attempt to do any deep processing to resolute the ambiguity. The mechanism people adopt to parse the ambiguity corpus is as same as the mechanism people apply to process the unambiguity corpus. In the second case, the ambiguity motivator appears in the region of the disambiguation region of the corpus. In this case, people will select the reanalysis mechanism to parse the corpus of the disambiguation and the subsequent regions. In the third case, the ambiguity motivator appears in the ambiguity region of the corpus. In this case, people will use the competition mechanism to parse the ambiguity corpus. In current paper, according to the motivator-based contingency model，three experiments were designed. In the three experiments, the English syntactic ambiguity corpus was used to investigate the mechanism that people explored to process the ambiguity corpus in three conditions which composed of the absence of the ambiguity motivator, the ambiguity motivator in the disambiguation region and ambiguity motivator in the ambiguity region. The task was self-paced word-by-word reading with a moving window display. Each trial began with a red “+” on the central of the screen for 300ms. Participants pressed the spacebar to reveal each word of the sentence. As each new word appeared, the preceding word disappeared. The amount of time the participant spent reading each word was recorded as the time between key-presses. After the final word of each item, a comprehension question appeared which asked about information contained in the sentence just read. Participants pressed one of two keys of “J” or “F” to respond ‘‘yes’’ or ‘‘no.’’ After an incorrect answer, the word ‘‘INCORRECT’’ flashed briefly on the screen. No feedback was given for correct responses. Participants were asked to read sentences at a natural rate and to be sure that they understood what they read. They were told to answer the questions as quickly and accurately as they could and to take wrong answers as an indication to read more carefully. A T test of determiner (ambiguity, control) on these reading time data was conducted. The data of the three experiments showed that when the ambiguity motivator didn’t appear in any region of the corpus, people would apply the mechanism that they used to parse the unambiguity corpus to process syntactic ambiguity coupus. When the ambiguity motivator appeared in the disambiguation region, people would adopt the reanalysis mechanism to parse the corpus of the disambiguiation and the subsequent region. When the ambiguity motivator appeared in the ambiguity region, people would select the competition mechanism to parse the ambiguity corpus. The conclusion is the motivator-based contingency model is applicable to predict and explain the resolution of syntactic ambiguity. People will follow the contingent properties of the ambiguity motivator to select mechanism to process the ambiguity corpus.