GRAIL—Generalized Representation and Aggregation of Information Layers

LREC (LAW) 2022  ·  Sameer Pradhan, Mark Liberman ·

This paper identifies novel characteristics necessary to successfully represent multiple streams of natural language information from speech and text simultaneously, and proposes a multi-tiered system that implements these characteristics centered around a declarative configuration. The system facilitates easy incremental extension by allowing the creation of composable workflows of loosely coupled extensions, or plugins, allowing simple intial systems to be extended to accomodate rich representations while maintaining high data integrity. Key to this is leveraging established tools and technologies. We demonstrate using a small example.

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