This is (probably) referring to feature vectors that indicate the "subcategorization frame," or immediate dependents, of the verb. For example, in the sentence "I saw the cat," the verb frame would indicate that "I" was a dependent on the left of "saw" and "cat" was a dependent on the right side of "saw." The feature vectors may also encode the type of relationship (i.e. that "I" is a noun subject and "cat" is a noun object) and/or encode the part-of-speech of the dependents rather than the words themselves.
--EDIT
I should mention that this is an operationalization of "subcategorization frame" that is slightly different from what syntacticians mean, which is why people usually say "frame-based" or "verb frame" instead of "subcategorization frame." NLP applications that exploit verb frames usually have a relatively shallow notion of syntax that results in more than one verb frame for some subcategorization frames. The passive alternation is usually ignored, for example, and so a verb in a passive sentence would have a different verb frame from the same verb in an active sentence, while syntactic analyses typically abstract over the passive alternation and use the same subcategorization frame for both sentences.
