Salesforce Com, Inc.

Michael Machado

Shashank Harinath

Jean-Marc Soumet

Qingqing Liu

Roojuta Lalani

Karl Ryszard Skucha

Thomas Archie Cook, Jr

Zineb Laraki

Manju Vijayakumar

Mike Rosenbaum

John Ball

Bryan McCann

Govardana Sachithanandam Ramachandran

Linwei Zhu

Yufan Xue

Abhishek Sharma

Approaches to using unstructured input to update heterogeneous data stores include receiving unstructured text input, receiving a template for interpreting the unstructured text input, identifying, using an entity classifier, entities in the unstructured text input, identifying one or more potential parent entities from the identified entities based on the template, receiving a selection of a parent entity from the one or more potential parent entities, identifying one or more potential child entities from the identified entities based on the template and the selected parent entity, receiving a selection of a child entity from the one or more potential child entities, identifying an action item in the unstructured text input based on the identified entities and the template, determining, using an intent classifier, an intent of the action item, and updating a data store based on the determined intent, the identified entities, and the selected child entity.

Using unstructured input to update heterogeneous data stores

A method for natural language processing includes receiving, by one or more processors, an unstructured text input. An entity classifier is used to identify entities in the unstructured text input. The identifying the entities includes generating, using a plurality of sub-classifiers of a hierarchical neural network classifier of the entity classifier, a plurality of lower-level entity identifications associated with the unstructured text input. The identifying the entities further includes generating, using a combiner of the hierarchical neural network classifier, a plurality of higher-level entity identifications associated with the unstructured text input based on the plurality of lower-level entity identifications. Identified entities are provided based on the plurality of higher-level entity identifications.

Systems and methods for named entity recognition

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San Francisco, CA, United States of America

Michael Machado