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From a user perspective, this exercise is much simpler than Gap Filling, however it was much more difficult to develop. To generate such exercise automatically we need to have correct part-of-speech tagger and then be able to convert a verb into its infinitive.
This is not completely trivial task as some verbs like e.g. to dog are exactly the same words as nouns and some verb forms like e.g lay have ambiguous infinitive form ‒ to lay or to lie in this case. You can know the difference from context and so must our system for automatic exercise generation.
You are presented with the excerpt from our corpus with almost all verbs which are in past tense form, past participle form or very rarely in simple present form converted to the bare infinitive and your job is to restore its original form. In this exercise you test not only how good you are in memorising 3 forms of the verb but you need also choose the relevant form for a given context. You need recognise correctly if given verb is regular or irregular, know how to glue propper past ending in case of regular verbs (is it -d or -ed?) and mind that some regular verbs are not so regular as you might think (with some short verbs like to nip, you must be careful to double the ending consonant ‒ in this case past form is nipped).
In this exercise we convert to infinitive almost all verbs except modal verbs (there will be separate exercise for them) and for a few verbs the probability to be converted to infinitive was intentionally lowered. On average, only one per tenth occurrences of be, say, do, have is converted to infinitive due the great frequency of these verbs in English literature. Except from that there is no bias in this exercise, so you are practising verb forms with their natural frequency as they occur in our corpus.