Amazon Technologies, Inc.

Kevin Michael Craft

Rama Krishna Sandeep Pokkunuri

Kalpesh N Sutaria

Stefano Stefani

Ameya Karnik

Bangrui Liu

Techniques to be used in natural language understanding (NLU) are described. For example, a NLU service to receive a request to analyze a written or spoken utterance; tokenize the received utterance; generate one or more labels corresponding to a substring of the tokenized received utterance, each of the labels including one or more slot types, by: for each path of a grammar-based finite state transducer (FST) data structure that includes instructions, traversing the path as far as possible for matches from a previous breakpoint, while maintaining i) locations of branching points and snapshots at those branching points and ii) an indication of which paths have been traversed, and recording a result of each path traversal as a generated label; resolve the one or more generated labels into machine-readable values; and output a result is described.

Slot type resolution process

Techniques for resolving a label are described. For example, a method of generating one or more labels corresponding to a substring of a tokenized utterance, each of the labels including one or more slot types, resolving the one or more generated labels into machine-readable values by: generating a tree of the generated one or more labels, the graph including a plurality of leaf nodes, wherein each rule of associated with a leaf node references a resolver, and resolving the generated tree from the leaf nodes to a root of the generated tree, by at each node, calling the referenced resolver and passing a result from each resolver to a subsequent resolver of the tree; and outputting a result of the resolving to an entity as dictated by the request is described.

Composite slot type resolution

Techniques for building slot types and slot type artifacts are described. For example, in some implementations, a natural language understanding (NLU) service is implemented by instructions that upon execution are to cause: receiving a request to build a slot type, the request including an indication of one or more locations storing information need to build a slot type, a slot type being a list of one or more values used to train a machine learning model to recognize a value for a slot; retrieving a slot type definition bundle associated with the request, the slot type definition bundle at least including a slot type definition defining resolution activities for the slot type; building the slot type using the retrieved slot type definition bundle; and storing into the storage slot type artifacts produced from building the slot type to be used during an analysis of an utterance.

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Seattle, WA, United States of America

Kevin Michael Craft