公开(公告)号：US09984684B1

公开(公告)日：2018-05-29

申请号：US13926844

申请日：2013-06-25

Applicant: Google LLC

Inventor： Jakob D. Uszkoreit ,  John Blitzer ,  Engin Cinar Sahin ,  Rahul Gupta ,  Dekang Lin ,  Fernando Pereira

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

CPC classification number: G10L15/1822 ,  G06F17/271 ,  G06F17/30424 ,  G06F17/30654 ,  G06F17/30864 ,  G10L15/26

Abstract: A language processing system collects similar queries and respective responses and aggregated by responses. Incorrect responses are determined and filtered by the aggregation. The remaining responses are then used to query a high precision system for attributes of entities specified by the queries. The attribute type is determined from the responses of the high precision system, and corresponding parse rules are generated. The parse rules are then associated with an operation that yields a response that specifies an attribute of the attribute type.

公开(公告)号：US11900068B1

公开(公告)日：2024-02-13

申请号：US18232112

申请日：2023-08-09

Applicant: GOOGLE LLC

Inventor： Matthew K. Gray ,  John Blitzer ,  Corinn Herrick ,  Srinivasan Venkatachary ,  Jayant Madhavan ,  Sam Oates ,  Phiroze Parakh ,  Aditya Shah ,  Mahsan Rofouei ,  Ibrahim Badr

IPC: G06F40/40 ,  G06F16/332

CPC classification number: G06F40/40 ,  G06F16/3328

Abstract: At least selectively utilizing a large language model (LLM) in generating a natural language (NL) based summary to be rendered in response to a query. In some implementations, in generating the NL based summary additional content is processed using the LLM. The additional content is in addition to query content of the query itself and, in generating the NL based summary, can be processed using the LLM and along with the query content—or even independent of the query content. Processing the additional content can, for example, mitigate occurrences of the NL based summary including inaccuracies and/or can mitigate occurrences of the NL based summary being over-specified and/or under-specified.

公开(公告)号：US20230342411A1

公开(公告)日：2023-10-26

申请号：US18000152

申请日：2022-03-09

Applicant: Google LLC

Inventor： Preyas Dalsukhbhai Popat ,  Gaurav Bhaskar Gite ,  John Blitzer ,  Jayant Madhavan ,  Aliaksei Severyn

IPC: G06F16/957 ,  G06F16/951

CPC classification number: G06F16/957 ,  G06F16/951

Abstract: Techniques of generating short answers for queries by a search engine include performing a training operation on a corpus of training data to train the score prediction engine, the corpus of training data including candidate passages providing short answers for display in callouts and remaining respective passages, from which a top scoring short answer is generated. In such implementations, the corpus of training data further includes the remaining respective passages and the respective titles of the candidate passage and remaining respective passages.

公开(公告)号：US20190278813A1

公开(公告)日：2019-09-12

申请号：US16416842

申请日：2019-05-20

Applicant: Google LLC

Inventor： Ashish Venugopal ,  Jakob D. Uszkoreit ,  John Blitzer ,  Edward Everett Anderson

IPC: G06F16/951 ,  G06F16/33

Abstract: The present disclosure relates to evaluating different semantic interpretations of a search query. One example method includes obtaining a set of search results for a particular search query submitted to a search engine; obtaining a set of semantic interpretations for the particular search query; obtaining, for each semantic interpretation of the set, a canonical search query; generating a modified search query based at least in part on the particular search query and the canonical search query for the semantic interpretation; obtaining a set of search results for the modified search query for the semantic interpretation; and determining, for each semantic interpretation of the set, a degree of similarity between (i) the set of search results of the modified search query for the semantic interpretation, and (ii) the set of search results for the particular search query.