US 11,900,061 B2
Intelligent interpretation of temporal expressions
Pamela Bhattacharya, Redmond, WA (US); Christopher Alan Meek, Kirkland, WA (US); Oleksandr Polozov, Seattle, WA (US); and Alex James Boyd, Longview, WA (US)
Assigned to Microsoft Technology Licensing, LLC, Redmond, WA (US)
Filed by MICROSOFT TECHNOLOGY LICENSING, LLC, Redmond, WA (US)
Filed on Apr. 14, 2021, as Appl. No. 17/230,300.
Prior Publication US 2022/0343079 A1, Oct. 27, 2022
Int. Cl. G06F 40/30 (2020.01); G06N 20/00 (2019.01); G06F 40/284 (2020.01)
CPC G06F 40/30 (2020.01) [G06F 40/284 (2020.01); G06N 20/00 (2019.01)] 15 Claims
OG exemplary drawing
 
1. A data processing system comprising:
a processor; and
a memory in communication with the processor, the memory comprising executable instructions that, when executed by, the processor, cause the data processing system to perform functions of:
receiving a request for natural language processing (NLP) of a content segment, the content segment including one or more temporal expressions;
accessing contextual data associated with each of the one or more temporal expressions;
parsing the content segment to identify one or more tokens in the content segment
generating predicted program tokens for an instance of a program in a domain-specific language;
generating the program in the domain-specific language, using an NLP model and based on the one or more tokens of the content segment and the predicted program tokens, the program describing a temporal logic of the content segment based on the one or more temporal expressions;
providing the program and contextual data as inputs to an interpreter;
executing the program using the interpreter to predict an intended time interval for the content segment; and
providing the intended time interval as an output,
wherein the NLP model is trained by using at least one of supervised learning and reinforcement learning.