Google Inc.

Jayakumar Hoskere

Chase Hensel

Rohit Ananthakrishna

Shruti Gupta

A set of candidate edits for a word of a sentence is obtained. Each of the set of candidate edits includes an edit word. Two or more surrounding words that each have a dependency relationship with the edit word are identified in the sentence. At least one of the two or more surrounding words is identified irrespective of their proximity to the edit word. The dependency relationship between the edit word and each of the surrounding words and the set of candidate edits is provided as input to a grammar accuracy prediction model. One or more outputs of the grammar accuracy prediction model are obtained. The one or more outputs indicate grammatical accuracy of each candidate edit from the set in the sentence in view of the dependency relationship with surrounding words. The candidate edit with highest accuracy is selected from the candidate edit set for the sentence.

Systems and methods to identify most suitable grammar suggestions among suggestions from a machine translation model

A server may receive an article that is retrieved from a server; determine whether the article satisfies first criteria based on content of the first article; annotate the article with a first article type when the article satisfies the first criteria; determine whether the article satisfies second criteria based on information associated with the article; annotate the article with a second article type when the article satisfies the second criteria; and store the article in association with a topic and at least one of the first article type or the second article type. The different server may be associated with a news website.

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Bengaluru, India

Jayakumar Hoskere