Schema Curation via Causal Association Rule Mining

Event schemas are structured knowledge sources defining typical real-world scenarios (e.g., going to an airport). We present a framework for efficient human-in-the-loop construction of a schema library, based on a novel mechanism for schema induction and a wellcrafted interface that allows non-experts to "program" complex event structures. Associated with this work we release a machine readable resource (schema library) of 232 detailed event schemas, each of which describe a distinct typical scenario in terms of its relevant sub-event structure (what happens in the scenario), participants (who plays a role in the scenario), fine-grained typing of each participant, and the implied relational constraints Figure 1: An example schema from our schema library, between them. Our custom annotation interface, induced from a skeleton mined by Causal ARM (Section SchemaBlocks, and the event schemas 3) and fully fleshed out by an annotator using our are available online.