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A method and device for modeling and named entity recognition based on maximum entropy model

A technology of maximum entropy model and named entity, which is applied in the fields of instrumentation, calculation, electrical digital data processing, etc., and can solve the problems of affecting recognition effect and information loss

Active Publication Date: 2016-07-20
NEW FOUNDER HLDG DEV LLC +2
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  • Claims
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Problems solved by technology

[0005] It can be seen from the existing technology that since this method is based on word segmentation for named entity recognition, word segmentation errors and the information loss caused by it will affect the recognition effect

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  • A method and device for modeling and named entity recognition based on maximum entropy model
  • A method and device for modeling and named entity recognition based on maximum entropy model
  • A method and device for modeling and named entity recognition based on maximum entropy model

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Embodiment Construction

[0031] In the technical solution of the specific embodiment of the present invention, the maximum entropy model is adopted, and a variety of linguistic information is fully utilized to directly label characters with roles to obtain a sequence of role labels with the highest probability, and through simple label name pattern matching, to Efficiently identifies named entities such as names of people, places, and organizations.

[0032] We believe that each character in a sentence implicitly carries a role information (role is an attribute of the character itself). The character role in the present invention is the role played by a single character in a named entity or sentence. Role labeling is to label the single-character roles in the sentence. These roles can be the first character of a place name (person's name), the last character of a place name (person's name) or the middle character of a place name (person's name), etc. For example, in the recognition of person names a...

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Abstract

The invention discloses a method for modeling and named entity recognition based on a maximum entropy model. The method includes: inputting a training text labeled with a named entity; performing role labeling on characters in the training text to obtain the character role labeling of the training text ; According to the character role labeling, the feature item of the character is established; the feature item of the character is input into the maximum entropy modeling tool, and the data model based on the character role labeling is obtained. The method does not need word segmentation, so it solves the problem of word segmentation error and the loss of information caused by it when performing named entity recognition, which affects the recognition effect.

Description

technical field [0001] The invention belongs to the category of natural language processing, and in particular relates to a method and device for modeling and named entity recognition based on a maximum entropy model. Background technique [0002] Named entity (NamedEntity, NE) refers to the named uniquely determined minimum information unit with specific meaning - proper name and quantity phrase, mainly including 7 types of named entities: person name, organization name, place name, date, time , currency values ​​and percentages. The task of named entity recognition is mainly to identify named entities in text and classify them. Named entity recognition was originally proposed as a subtask at the MUC-6 (Message Understanding Conference Message Understanding Workshop). From the overall research results of named entity recognition, the recognition of date, time, currency value, and percentage is relatively simple. The design of rules and statistical training of data are als...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F17/27
Inventor 王学武彭学政杨建武肖建国
Owner NEW FOUNDER HLDG DEV LLC
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