  Typical spoken language understanding systems provide narrow semantic parses
using a domain-specific ontology. The parses contain intents and slots that are
directly consumed by downstream domain applications. In this work we discuss
expanding such systems to handle compound entities and intents by introducing a
domain-agnostic shallow parser that handles linguistic coordination. We show
that our model for parsing coordination learns domain-independent and
slot-independent features and is able to segment conjunct boundaries of many
different phrasal categories. We also show that using adversarial training can
be effective for improving generalization across different slot types for
coordination parsing.
