In semantic parsing, natural language questions map to meaning representation language (MRL) expressions over some fixed vocabulary of predicates. To do this reliably, one must guarantee that for a wide class of natural language questions (the so called semantically tractable questions), correct interpretations are always in the mapped set of possibilities. Here we demonstrate the system COVER which significantly clarifies, revises and extends the notion of semantic tractability. COVER is written in Python and uses NLTK.