公开(公告)号：US12265528B1

公开(公告)日：2025-04-01

申请号：US18187553

申请日：2023-03-21

Applicant: Amazon Technologies, Inc.

Inventor： Wuwei Lan ,  Patrick Ng ,  Zhiguo Wang ,  Ramesh M. Nallapati ,  Henghui Zhu ,  Anuj Chauhan ,  Sudipta Sengupta ,  Stephen Michael Ash ,  Bing Xiang ,  Gregory David Adams

IPC: G06F16/00 ,  G06F16/22 ,  G06F16/242 ,  G06F16/2457 ,  G06F16/248 ,  G06F16/25 ,  G06N3/0455 ,  G06N3/0499

Abstract: Techniques for handling natural language query processing are described. In some examples, a sequence-to-sequence model is used to handle a natural language query. Post-processing of a result of the sequence-to-sequence model utilizes fine-grained information from an entity linker. In some examples, the sequence-to-sequence model and aspects of a natural language query pipeline are used to handle a natural language query.

公开(公告)号：US12259914B1

公开(公告)日：2025-03-25

申请号：US17240724

申请日：2021-04-26

Applicant: Amazon Technologies, Inc.

Inventor： Yifan Gao ,  Henghui Zhu ,  Ramesh M. Nallapati ,  Patrick Ng ,  Cicero Nogueira Dos Santos ,  Zhiguo Wang ,  Feng Nan ,  Dejiao Zhang ,  Andrew Oliver Arnold ,  Bing Xiang

IPC: G06F16/332 ,  G06F16/3329 ,  G06F40/20 ,  G06N3/045 ,  G06N5/04 ,  G06N20/00

Abstract: Techniques for predicting an answer to a question using a machine learning model are described. In some examples, the model predicts one or more answers to the question by: predicting at least two answers to the question using a first component of the question-answer model from a set of passages, generating, using a second component of the question-answer model, at least one question for each of the predicted at least two answers, and performing roundtrip predictions until each generated question only has one answer.

公开(公告)号：US12062368B1

公开(公告)日：2024-08-13

申请号：US17039613

申请日：2020-09-30

Applicant: Amazon Technologies, Inc.

Inventor： Anuroop Arora ,  Atul Deo ,  Ramesh M. Nallapati ,  Henghui Zhu ,  Arvind Arikatla ,  Sai Bharadwaj Kanduri ,  Srikanth Prabala ,  Dejiao Zhang

IPC: G10L15/18 ,  G06N20/00 ,  G06Q30/01 ,  G10L15/06 ,  G10L15/08 ,  G10L15/26

CPC classification number: G10L15/1822 ,  G06N20/00 ,  G10L15/063 ,  G10L15/26 ,  G06Q30/01 ,  G10L2015/0631 ,  G10L2015/088

Abstract: Systems and methods to detect themes in contacts data. Contacts data may be encoded as text (e.g., chat logs), audio (e.g., audio recordings), and various other modalities. Text-based transcripts of contacts data may be parsed into turns, an issue turn may be detected using a machine learning model, a key phrase may be extracted from the issue turn. Key phrases from across multiple contacts data may be clustered to identify themes.