Retrieving a word in a sentence requires speakers to overcome syntagmatic, as well as paradigmatic interference. When accessing cat in "The cat chased the string," not only are similar competitors such as dog and cap activated, but also other words in the planned sentence, such as chase and string. We hypothesize that both types of interference impact the same stage of lexical access, and review connectionist models of production that use an error-driven learning algorithm to overcome that interference. This learning algorithm creates a mechanism that limits syntagmatic interference, the syntactic "traffic cop," a configuration of excitatory and inhibitory connections from syntactic-sequential states to lexical units. We relate the models to word and sentence production data, from both normal and aphasic speakers.