Google Inc.

Marius Pasca

Enrique Alfonseca

Enrique Robledo-Arnuncio

Lev Finkelstein

Fernando Pereira

Benjamin Van Durme

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for extracting instance attributes from text are described. In one aspect, a method exploits weakly-supervised and unsupervised instance relatedness data, available in the form of labeled classes of instances and distributionally similar instances. The method organizes the data into a graph containing instances, class labels, and attributes. The method propagates attributes among related instances, through random walks over the graph.

Extracting instance attributes from text

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for extracting semantic classes and corresponding instances from a collection of text. One aspect of the subject matter described in this specification can be embodied in methods that include the actions of receiving a collection of text; identifying an initial collection of instance-class pairs for the collection of text; clustering a collection of semantically similar phrases using the collection of text; generating, using one or more processors, an extracted collection of instance-class pairs using the initial collection of instance-class pairs and the semantically similar phrase clusters; and storing the extracted collection of instance-class pairs for use in information retrieval.

Extracting semantic classes and instances from text

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for extracting and scoring class-instance pairs. One method includes applying extraction patterns to document text to derive class-instance pairs, determining a frequency score and a diversity score for each distinct class-instance pair, and determining a pair score for each class-instance pair from the frequency score and the diversity score. Another method includes applying extraction patterns to document text to derive candidate class-instance pairs, determining, for each distinct candidate class-instance pair, a number of distinct phrases from which the distinct candidate class-instance pair was derived, and determining a pair score for each distinct candidate class-instance pair from the number of distinct phrases from which the candidate class-instance pair was extracted.

Extracting and scoring class-instance pairs

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating query suggestions. In one aspect, a method includes receiving candidate text queries and class instance pairs and generating one or more query specializations from the candidate text queries and the class instance pairs. In another aspect, a method includes receiving a partial query entered by a user, identifying one or more query specializations for query completions for the partial query, and presenting query suggestions to the user, including presenting the identified query specializations.

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Marius Pasca