Schema Curation via Causal Association Rule Mining

• URL: http://arxiv.org/abs/2104.08811v1
• Date: Sun, 18 Apr 2021 10:48:26 GMT
• Title: Schema Curation via Causal Association Rule Mining
• Authors: Noah Weber, Anton Belyy, Nils Holzenberger, Rachel Rudinger, Benjamin Van Durme
• Abstract summary: Event schemas are structured knowledge sources defining typical real-world scenarios. We present a framework for efficient human-in-the-loop construction of a schema library.
• Score: 41.853476604903356
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: 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 well-crafted 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 between them. Our custom annotation interface, SchemaBlocks, and the event schemas are available online.

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