公开(公告)号：US20200090034A1

公开(公告)日：2020-03-19

申请号：US16134959

申请日：2018-09-18

Applicant: salesforce.com, inc.

Inventor： Govardana Sachithanandam RAMACHANDRAN ,  Shashank HARINATH ,  Abhishek SHARMA ,  Jean-Marc SOUMET ,  Michael MACHADO ,  Bryan MCCANN

IPC: G06N3/08 ,  G10L15/16 ,  G10L15/06 ,  G06F17/30

Abstract: For a database system accessible by one or more users, a neural network model and related method are provided that allow a user of the database system to provide unstructured input in the form of a verbal or textual narrative or utterance that expresses the information in a language and manner that is more comfortable for the user. A portion of the narrative or utterance may relate to one or action items that the user intends to be taken with respect to the database system, such as creating, updating, modifying, or deleting a database item (e.g., contact, calendar item, deal, etc.). The neural model processes the unstructured input (narrative or utterance) and determines or classifies the intent with respect to the action item for the database.

公开(公告)号：US20200089757A1

公开(公告)日：2020-03-19

申请号：US16134956

申请日：2018-09-18

Applicant: salesforce.com, inc.

Inventor： Michael MACHADO ,  John BALL ,  Thomas Archie COOK, JR. ,  Shashank HARINATH ,  Roojuta LALANI ,  Zineb LARAKI ,  Qingqing LIU ,  Mike ROSENBAUM ,  Karl Ryszard SKUCHA ,  Jean-Marc SOUMET ,  Manju VIJAYAKUMAR

IPC: G06F17/27 ,  G06F17/30 ,  G10L15/22 ,  G10L15/18

Abstract: 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.

公开(公告)号：US20210209305A1

公开(公告)日：2021-07-08

申请号：US17211162

申请日：2021-03-24

Applicant: salesforce.com, inc.

Inventor： Michael MACHADO ,  John BALL ,  Thomas Archie COOK, JR. ,  Shashank HARINATH ,  Roojuta LALANI ,  Zineb LARAKI ,  Qingqing LIU ,  Mike ROSENBAUM ,  Karl Ryszard SKUCHA ,  Jean-Marc SOUMET ,  Manju VIJAYAKUMAR

IPC: G06F40/295 ,  G06F16/332 ,  G06F40/30 ,  G10L15/18 ,  G10L15/22

Abstract: 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.

公开(公告)号：US20200090033A1

公开(公告)日：2020-03-19

申请号：US16134957

申请日：2018-09-18

Applicant: salesforce.com, inc.

Inventor： Govardana Sachithanandam RAMACHANDRAN ,  Michael MACHADO ,  Shashank HARINATH ,  Linwei ZHU ,  Yufan XUE ,  Abhishek SHARMA ,  Jean-Marc SOUMET ,  Bryan MCCANN

IPC: G06N3/08 ,  G06F17/30 ,  G06F17/20

Abstract: 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.