Learning to extract entities from conversations with neural networks
US12216999B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Feb 19, 2020 |
| Grant date | Feb 4, 2025 |
| Priority date | — |
| Expiry date | Mar 30, 2042 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F40/279
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for extracting entities from conversation transcript data. One of the methods includes obtaining a conversation transcript sequence, processing the conversation transcript sequence using a span detection neural network configured to generate a set of text token spans; and for each text token span: processing a span representation using an entity name neural network to generate an entity name probability distribution over a set of entity names, each probability in the entity name probability distribution representing a likelihood that a corresponding entity name is a name of the entity referenced by the text token span; and processing the span representation using an entity status neural network to generate an entity status probability distribution over a set of entity statuses.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.