Stanford NER provides 7class model to recognize PERSON, LOCATION, ORGANIZATION, DATE, TIME, PERCENT, MONEY. In previous blogs, we have discussed 3class model example. In this article, we will discuss 7class model with an example.

Steps:

Step 1: Download  Stanfordner-zip file.

Step 2: Extract Stanford bundle, add stanfor-ner jar file into your project classpath.

Step 3: write below code snippets

//path of classifier we want to load
String classierPath = "D:\\classifiers\\english.muc.7class.distsim.crf.ser.gz";

//content that we want to classify
String fileContents = "\"barak Obama was born in 1961 in Honolulu, Hawaii,\" in 1988 Obama enrolled in Harvard Law School. My friend got 98% in 10th standard.";

//Load classifier , classifier should be load only one time
AbstractSequenceClassifier classifier = CRFClassifier.getClassifierNoExceptions(classierPath);

//classify the text
List<List<CoreLabel>> out = classifier.classify(fileContents);

//iterate the result and print it.
for (List<CoreLabel> sentence : out) {
    for (CoreLabel word : sentence) {
        //unclassify label class is O , we will not print it here
        if(word.getString(CoreAnnotations.AnswerAnnotation.class).equals("O"))
            continue;
        System.out.println(word.word() + " = " + word.get(CoreAnnotations.AnswerAnnotation.class) );
    }

}

output:

Loading classifier from D:\classifiers\english.muc.7class.distsim.crf.ser.gz ... done [7.1 sec].
Obama = PERSON
1961 = DATE
Honolulu = LOCATION
Hawaii = LOCATION
1988 = DATE
Harvard = ORGANIZATION
Law = ORGANIZATION
School = ORGANIZATION
98 = PERCENT
% = PERCENT

Stanford NER live demo output:

Standford NER 7class model livener output

Refer Live demo , Stanford CRF , CoreNLP annotators for details.

 

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