Semantic Parsing for Task Oriented Dialog using Hierarchical Representations

Previous work on task oriented intent and slot-filling work has been restricted to one intent per query and one slot label per token, and thus cannot model complex compositional requests. Alternative semantic parsing systems have represented queries as logical forms, but these are challenging to annotate and parse. We propose a hierarchical annotation scheme for semantic parsing that allows the representation of compositional queries, and can be efficiently and accurately parsed by standard constituency parsing models. We release a dataset of 44k annotated queries 1,

Typical systems classify the intent of a query (e.g. GET DIRECTIONS) and tag the necessary slots (e.g. San Francisco) (Mesnil et al., 2013; Liu and Lane, 2016). It is difficult for such representations to adequately represent nested queries such as “Driving directions to the Eagles game”, which is composed of GET DIRECTIONS and GET EVENT intents. We explore a hierarchical representation for such queries, which dramatically improves the expressive power while remaining accurate and efficient to annotate and parse (see Figure 1).