A computational model of tense selection and its experimentation within an intelligent tutor
The paper presents a new computational model for the selection of verb tenses aimed at supporting the choice and conjugation of the appropriate tense in English sentences. The work has been developed within the framework of the ET research project whose purpose is the experimentation of intelligent tutoring systems for foreign language teaching. The model has been validated and experimentally tested through the development of TEN-EX (TENse EXpert), a prototype system which receives in input a representation of an English sentence and is capable of finding and conjugating the appropriate tense(s) for it. The model originates from the functional-systemic approach to tense from which it inherits the basic ideas of tense opposition and seriality. The model is characterized by some original assumptions such as the partitioning of the tense selection process in two separate phases aimed at discovering the ‘objective’ tense, relating speaking time to event time, and at mapping the objective tense into the actual grammatical tense. This bipartite organization corresponds to the idea that the tense selection process is influenced by both the temporal semantics of the situation a speaker intends to describe and the pragmatic and syntactic features which act as a filter in mapping the objective tense into the grammatical resources of the language at hand. TEN-EX is a fully implemented system which is currently capable of solving more than 80 exercises covering all the English indicative tenses.
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