公开(公告)号：US11526557B2

公开(公告)日：2022-12-13

申请号：US16697979

申请日：2019-11-27

Applicant: Amazon Technologies, Inc.

Inventor： Zhiguo Wang ,  Zhiheng Huang ,  Ramesh M. Nallapati ,  Bing Xiang

IPC: G06F16/9038 ,  G06F16/908 ,  G06F16/93 ,  G06N20/00

Abstract: Techniques for displaying a search are described. An exemplary method includes receiving a search query, performing the search query on a plurality of documents, the documents including text passages, to generate a search query result, determining an aspect of the search query result that has a confidence value that exceeds a first confidence threshold with respect to its relevance to the search query; and, displaying the search result including an emphasis on the aspect of the result exceeds the first confidence threshold.

公开(公告)号：US11475067B2

公开(公告)日：2022-10-18

申请号：US16698080

申请日：2019-11-27

Applicant: Amazon Technologies, Inc.

Inventor： Cicero Nogueira Dos Santos ,  Xiaofei Ma ,  Peng Xu ,  Ramesh M. Nallapati ,  Bing Xiang ,  Sudipta Sengupta ,  Zhiguo Wang ,  Patrick Ng

IPC: G06F40/30 ,  G06F16/9032 ,  G06K9/62 ,  G06F16/9038 ,  G06N20/00 ,  G06F16/903 ,  G06F16/93 ,  G06F40/20

Abstract: Techniques for generation of synthetic queries from customer data for training of document querying machine learning (ML) models as a service are described. A service may receive one or more documents from a user, generate a set of question and answer pairs from the one or more documents from the user using a machine learning model trained to predict a question from an answer, and store the set of question and answer pairs generated from the one or more documents from the user. The question and answer pairs may be used to train another machine learning model, for example, a document ranking model, a passage ranking model, a question/answer model, or a frequently asked question (FAQ) model.

公开(公告)号：US11366855B2

公开(公告)日：2022-06-21

申请号：US16697948

申请日：2019-11-27

Applicant: Amazon Technologies, Inc.

Inventor： Jean-Pierre Dodel ,  Zhiheng Huang ,  Xiaofei Ma ,  Ramesh M. Nallapati ,  Krishnakumar Rajagopalan ,  Milan Saini ,  Sudipta Sengupta ,  Saurabh Kumar Singh ,  Dimitrios Soulios ,  Ankit Sultania ,  Dong Wang ,  Zhiguo Wang ,  Bing Xiang ,  Peng Xu ,  Yong Yuan

IPC: G06F16/00 ,  G06F16/901 ,  G06N3/04 ,  G06F16/2457 ,  G06F16/903

Abstract: Techniques for searching documents are described. An exemplary method includes receiving a document search query; querying at least one index based upon the document search query to identify matching data; fetching the identified matched data; determining one or more of a top ranked passage and top ranked documents from the set of documents based upon one or more invocations of one or more machine learning models based at least on the fetched identified matched data and the document search query; and returning one or more of the top ranked passage and the proper subset of documents.

公开(公告)号：US12271698B1

公开(公告)日：2025-04-08

申请号：US17537273

申请日：2021-11-29

Applicant: Amazon Technologies, Inc.

Inventor： Jun Wang ,  Sudipta Sengupta ,  Zhiguo Wang ,  Ramesh M Nallapati ,  Bing Xiang

IPC: G06F40/295 ,  G06F16/2452 ,  G06F16/2458 ,  G06F40/284

Abstract: A schema and cell value aware Named Entity Recognition (NER) model is used to perform natural language queries. Natural language queries may be received via an interface of a natural language query processing system. A fuzzy search may be performed that allows non-exact matches for column names or cell values of data sets potentially used to answer the natural language query. An NER model that adds a type embedding for an exact match of a column name or cell found in the fuzzy search that corresponds to a span of one or more words may be applied as part of generating the entity prediction for the natural language query. One or more queries to at least one of the data sets may be performed to return a result to the natural language query using the entity prediction generated by the NER machine learning model.

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：US20230325384A1

公开(公告)日：2023-10-12

申请号：US18182303

申请日：2023-03-10

Applicant: Amazon Technologies, Inc.

Inventor： Ramesh M Nallapati ,  Zhiguo Wang ,  Bing Xiang ,  Patrick Ng ,  Yung Haw Wang ,  Mukul Karnik ,  Nanyan Li ,  Sharanabasappa Parashuram Revadigar ,  Timothy Jones ,  Stephen Michael Ash ,  Sudipta Sengupta ,  Gregory David Adams ,  Deepak Shantha Murthy ,  Douglas Scott Cerny ,  Stephanie Weeks ,  Hanbo Li

IPC: G06F16/2452 ,  G06F16/242 ,  G06F40/295 ,  G06N20/00

CPC classification number: G06F16/24522 ,  G06F16/243 ,  G06F16/2423 ,  G06F40/295 ,  G06N20/00

Abstract: Interactive assistances for executing natural language queries to data sets may be performed. A natural language query may be received. Candidate entity linkages may be determined between an entity recognized in the natural language query and columns in data sets. The candidate linkages may be ranked according to confidence scores which may be evaluated to detect ambiguity for an entity linkage. Candidate entity linkages may be provided to a user via an interface to select an entity linkage to use as part of completing the 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：US12007988B2

公开(公告)日：2024-06-11

申请号：US18182303

申请日：2023-03-10

Applicant: Amazon Technologies, Inc.

Inventor： Ramesh M Nallapati ,  Zhiguo Wang ,  Bing Xiang ,  Patrick Ng ,  Yung Haw Wang ,  Mukul Karnik ,  Nanyan Li ,  Sharanabasappa Parashuram Revadigar ,  Timothy Jones ,  Stephen Michael Ash ,  Sudipta Sengupta ,  Gregory David Adams ,  Deepak Shantha Murthy ,  Douglas Scott Cerny ,  Stephanie Weeks ,  Hanbo Li

IPC: G06F16/2452 ,  G06F16/242 ,  G06F40/295 ,  G06N20/00

CPC classification number: G06F16/24522 ,  G06F16/2423 ,  G06F16/243 ,  G06F40/295 ,  G06N20/00

Abstract: Interactive assistances for executing natural language queries to data sets may be performed. A natural language query may be received. Candidate entity linkages may be determined between an entity recognized in the natural language query and columns in data sets. The candidate linkages may be ranked according to confidence scores which may be evaluated to detect ambiguity for an entity linkage. Candidate entity linkages may be provided to a user via an interface to select an entity linkage to use as part of completing the natural language query.

公开(公告)号：US11726994B1

公开(公告)日：2023-08-15

申请号：US17219694

申请日：2021-03-31

Applicant: Amazon Technologies, Inc.

Inventor： Jun Wang ,  Zhiguo Wang ,  Sharanabasappa Parashuram Revadigar ,  Ramesh M Nallapati ,  Bing Xiang ,  Sudipta Sengupta ,  Yung Haw Wang

IPC: G06F16/242 ,  G06F16/2452 ,  G06F16/28 ,  G06F16/248 ,  G06F16/2457

CPC classification number: G06F16/243 ,  G06F16/248 ,  G06F16/24522 ,  G06F16/24573 ,  G06F16/287

Abstract: Query restatements may be provided for explaining natural language query results. A natural language query is received at a natural language query processing system. An intermediate representation of the natural language query is generated for executing the natural language query. The intermediate representation is translated into a natural language restatement of the natural language query. The natural language restatement is provided with a result of the natural language query via an interface of the natural language query processing system.

公开(公告)号：US11500865B1

公开(公告)日：2022-11-15

申请号：US17219706

申请日：2021-03-31

Applicant: Amazon Technologies, Inc.

Inventor： Jun Wang ,  Zhiguo Wang ,  Sharanabasappa Parashuram Revadigar ,  Ramesh M Nallapati ,  Bing Xiang ,  Stephen Michael Ash ,  Timothy Jones ,  Sudipta Sengupta ,  Rishav Chakravarti ,  Patrick Ng ,  Jiarong Jiang ,  Hanbo Li ,  Donald Harold Rivers Weidner

IPC: G06F7/00 ,  G06F16/2452 ,  G06F40/295 ,  G06N20/00 ,  G06F16/242

Abstract: Multiple stage filtering may be implemented for natural language query processing pipelines. Natural language queries may be received at a natural language query processing system and processed through a query language processing pipeline. The query language processing pipeline may filter candidate linkages for a natural language query before performing further filtering of the candidate linkages in the natural language query processing pipeline as part of generating an intermediate representation used to execute the natural language query.