Sentence comprehension involves timely computing different types of relations between its verbs and noun arguments, such as morphosyntactic, semantic, and thematic relations. Here, we used EEG technique to investigate the potential differences in thematic role computing and lexical-semantic relatedness processing during on-line sentence comprehension, and the interaction between these two types of processes. Mandarin Chinese sentences were used as materials. The basic structure of those sentences is “Noun+Verb+‘le’+a two-character word”, with the Noun being the initial argument. The verb disambiguates the initial argument as an agent or a patient. Meanwhile, the initial argument and the verb are highly or lowly semantically related. The ERPs at the verbs revealed that: relative to the agent condition, the patient condition evoked a larger N400 only when the argument and verb were lowly semantically related; however, relative to the high-relatedness condition, the low-relatedness condi)