Complex conjunctions and determiners are often considered as pretokenized units in parsing. This is not always realistic, since they can be ambiguous. We propose a model for joint dependency parsing and multiword expressions identification, in which complex function words are represented as individual tokens linked with morphological dependencies. Our graph-based parser includes standard second-order features and verbal subcategorization features derived from a syntactic lexicon. We train it on a modified version of the French Treebank enriched with morphological dependencies. It recognizes 81.79% of ADV-que conjunctions with 91.57% precision, and 82.74% of de-DET determiners with 86.70% precision.