Google Inc.

David Lecomte

Othar Hansson

Jonathan James Effrat

Christina R Dhanaraj

Luuk Van Dijk

Steffen Gerd Meschkat

Radu Jurca

Lode Vandevenne

Matsvei Zhdanovich

Christopher Semturs

Anja Hauth

Ivan Zauharodneu

Alexander Lyashuk

Sebastian Steiger

Henrik Grimm

Nathanael Martin Schärli

Danila Sinopalnikov

Computer-implemented systems and methods are provided for extracting and storing information regarding entities from documents, such as webpages. In one implementation, a system is provided that detects an entity candidate in a document and determines that the detected candidate is a new entity. The system also detects a known entity proximate to the known entity based on the one or more entity models. The system also detects a context proximate to the new and known entities having a lexical relationship to the known entity. The system also determines a second entity class associated with the known entity and a context class associated with the context. The system also generates a first entity class based on the second entity class and the context class. The system also generates an entry in the one or more entity models reflecting an association between the new entity and the first entity class.

Computerized systems and methods for extracting and storing information regarding entities

Computer-implemented systems and methods are disclosed for building knowledge bases, such as knowledge graphs, using context clouds. According to certain embodiments, a target object is identified in a portion of unstructured or semi-structured data in a target document, which does not conform to a predefined structure or pattern. A knowledge server may build a context cloud for the target document. The knowledge server may analyze one or more other documents stored in a networked database, to identify candidate documents that may include a meaning or relationship associated with the target object. The knowledge server may analyze one or more context clouds for the candidate documents to determine a meaning or relationship of the target object based on objects in the candidate document(s). The knowledge server may associate the determined meanings and/or relationships with the target object in the target document, thereby creating a new portion of a knowledge graph.

Computerized systems and methods for building knowledge bases using context clouds

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for identifying answer boxes for presentation to a user. In general, one aspect of the subject matter described in this specification can be embodied in methods that include the actions of, while receiving an input entered in a search engine query input field by a first user, and before the first user has submitted the input as a search request, obtaining content for an answer box for the input and presenting the answer box to the first user. The answer box can be an answer box associated with a dominant query for the input, or can be an answer box identified from historical answer box data for the input.

Framework for selecting and presenting answer boxes relevant to user input as query suggestions

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for identifying geographic features. In one aspect, a method includes receiving a query. Geographic features are identified, each geographic feature being associated with one or more names, each geographic feature being associated with at least one name that includes the query. A feature-query score is computed for each geographic feature, including: for each name of the geographic feature that includes the query, identifying a computed feature-name score, wherein the feature-name score is computed based on a count of a number of occurrences of the name in a query log, wherein each occurrence is attributed to the feature; and computing the feature-query score based on the identified feature-name scores. The geographic features are ranked according to the feature-query scores.

Identifying geographic features from query prefixes

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Zurich, Switzerland

David Lecomte