Recently, cross-situational word learning (XSL) has gained attention as a viable mechanism for learning the meaning of words. XSL refers to the tracking of wordreferent pairs over a series of different exposures (Siskind, 1996; Yu & Smith, 2007). However, it has recently been suggested that word learning likely functions by the extraction of information from several cues, such as perceptual statistical, social, and linguistic (Hirsh-Pasek, Golinkoff, & Hollich, 2000). In this work, I measured the contribution of co-occurrence frequencies (statistical cues) and syntactic-semantic (linguistic cues) links in a sentential XSL experiment that contained both nouns and verbs. Participants were exposed to three different learning conditions that varied in the mode of presentation. Participants either learned nouns and verbs together in one phase (unstaggered learning), or learned in two phases, initially learning the subset of nouns (staggered-with-nouns) or verbs (staggered-with-verbs) first. With unstaggered learning, participants could use primarily only XSL, while with staggered learning, participants could use both XSL and syntactic bootstrapping. Results demonstrated that the combination of syntactic bootstrapping and XSL significantly facilitated word learning. The results support an integrative and comprehensive model of word learning (e.g. Hirsh-Pasek et al., 2000). In the general discussion, the relationship between an integrative view of language and a domain-general account of language is discussed.