US 8,478,787 B2 · Name detection

Abstract

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for name detection. A method includes generating a raw name detection model using a collection of family names and an annotated corpus including a collection of n-grams. The method includes applying the raw name detection model to a collection of semi-structured data to form annotated semi-structured data identifying n-grams identifying names and n-grams not identifying names and applying the raw name detection model to a large unannotated corpus to form a large annotated corpus data identifying n-grams of the large unannotated corpus identifying names and n-grams not identifying names. The method includes generating a name detection model, including deriving a name model using the annotated semi-structured data identifying names and the large annotated corpus data identifying names, deriving a not-name model using the semi-structured data not identifying names, and deriving a language model using the large annotated corpus.

Claims30

Dependent claims

A method implemented by data processing apparatus, the method comprising:

generating a raw name detection model using a collection of family names and an annotated corpus including a collection of n-grams, each n-gram having a corresponding probability of occurring as a respective name in the annotated corpus;
applying the raw name detection model to a collection of semi-structured data to form annotated semi-structured data, the annotated semi-structured data identifying n-grams identifying names and n-grams not identifying names;
applying the raw name detection model to a large unannotated corpus to form a large annotated corpus data identifying n-grams of the large unannotated corpus identifying names and n-grams not identifying names;
and
generating a name detection model including:
deriving a name model using the annotated semi-structured data identifying names and the large annotated corpus data identifying names,
deriving a not-name model using the semi-structured data not identifying names,
deriving a language model using the large annotated corpus;
and
wherein generating and applying are performed by data processing apparatus.

7 more elements

A computer program product, stored on a machine-readable storage device that, when executed by data processing apparatus, causes the data processing apparatus to perform operations comprising:

generating a raw name detection model using a collection of family names and an annotated corpus including a collection of n-grams, each n-gram having a corresponding probability of occurring as a respective name in the annotated corpus;
applying the raw name detection model to a collection of semi-structured data to form annotated semi-structured data, the annotated semi-structured data identifying n-grams identifying names and n-grams not identifying names;
applying the raw name detection model to a large unannotated corpus to form a large annotated corpus data identifying n-grams of the large unannotated corpus identifying names and n-grams not identifying names;
and
generating a name detection model including:
deriving a name model using the annotated semi-structured data identifying names and the large annotated corpus data identifying names,
deriving a not-name model using the semi-structured data not identifying names, and
deriving a language model using the large annotated corpus.

5 more elements

A system comprising:

a machine-readable storage device having instructions stored thereon;
and
data processing apparatus programmed to execute the instructions to perform operations comprising:
generating a raw name detection model using a collection of family names and an annotated corpus including a collection of n-grams, each n-gram having a corresponding probability of occurring as a respective name in the annotated corpus;
applying the raw name detection model to a collection of semi-structured data to form annotated semi-structured data, the annotated semi-structured data identifying n-grams identifying names and n-grams not identifying names;
applying the raw name detection model to a large unannotated corpus to form a large annotated corpus data identifying n-grams of the large unannotated corpus identifying names and n-grams not identifying names;
and
generating a name detection model including:
deriving a name model using the annotated semi-structured data identifying names and the large annotated corpus data identifying names,
deriving a not-name model using the semi-structured data not identifying names, and
deriving a language model using the large annotated corpus.

8 more elements

Dependencies are inferred from the claim text.

Name detection

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Name detection

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Abstract

Claims30