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guokr / stan-cn-ner

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A Chinese naming entity recognization package in stan-cn-* family

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java
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stan-cn-ner

stan-cn-* family are wrappers based on Stanford CoreNLP for the convenience of Chinese users. This package provide a Chinese naming entity recognizor.

stan-cn-* family are including:

  • stan-cn-com: Common code base
  • stan-cn-seg: Chinese segmentation and related data model
  • stan-cn-ner: Naming entity recognization and related data model
  • stan-cn-tag: POS tagging and related data model

Purpose of the package

The original Stanford CoreNLP packages with default language settings in Maven central is only for English. If you are dealing with simplified Chinese, you still need to download the Chinese model and fix some configuration files.

The burden is not too much, but if you deploy these packages to a server cluster, this burden might be amplified.

Whatever you face a single node or a server farm, it would be a pleasurable solution to provide packages with default settings of Chinese language models. That is what we do.

Comments, reviews, bug reports and patches are welcomed.

Current version

Current version is 0.0.6 and based on Stanford CoreNLP 3.4 with minor fixes.

including below dependency:

  • maven:
    <dependency>
        <groupId>com.guokr</groupId>
        <artifactId>stan-cn-ner</artifactId>
        <version>0.0.6</version>
    </dependency>
  • leiningen:
    [com.guokr/stan-cn-ner "0.0.6"]
  • sbt:
    libraryDependencies += "com.guokr" % "stan-cn-ner" % "0.0.6"

Simplified API

We use a very simple API to reduce the complexity.

    new NerWrapper(settings).recognize(text);

Or if you want to use the default language models, just use

    __NER__.INSTANCE.recognize(text);

Preparation for release

Before release this package to maven central, please execute below commands:

  • mvn clean source:jar javadoc:jar package
  • export MAVEN_OPTS=-Xmx2048m
  • mvn release:clean
  • mvn release:prepare
  • mvn release:perform

Authors

License

GPLv2, just same as the license of Stanford CoreNLP package

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