On feature-based vocabulary selection mechanisms in late insertion: third person number agreement in the French future tense

We propose that feature bundles in syntactic computations coactivate subset vocabulary items in content-based access. Thus, in French, an inflectional node for the future tense bearing [Number: Plural] activates third-person singular -a underspecified for [Number: Ø] and third- person plural -ont specified for [Number: Plural]. These activations compete in externalization. [Number: Ø/Plural] defines a scale where plural-marked -ont carries more information than -a, allowing scalar inferencing in form selection. Given an activated Plural-marked -ont, -a (3ps.sg) is automatically interpreted as [–Plural] via scalar inferencing and becomes unsuitable for insertion. Thus, -ont (3ps.pl) must be selected when -a (3ps.sg) is eliminated. We tested our model assuming an interaction of cross-domain inferencing with morphological selection, using two experiments. In forced-paced reading and listening tasks, 19 native speaker subjects per task classified picture probes accompanying matching and mismatching subject-verb future tense agreement. Classification times for pictures semantically linked to the verb probed for an interaction between the processing of agreement morphology and the ongoing conceptual processing of the sentence. Classification times were modulated by the type of morphological mismatch. Singular verb form mangera (eat-fut.3ps.sg) in plural contexts slowed down picture classifications, whereas plural verb form mangeront (eat-fut.3ps.pl) in singular contexts did not. This specific interaction between purely formal agreement and conceptual-structure processing is unexplained by superset models of late insertion, or by interface relations, frequency, load of stored information, and phonological cohort activation. It suggests that domain-general principles of inference enrich domain-specific feature-based computations accessing vocabulary items through the coactivation of features.