opennlp v2.0.2

NodeJs OpenNLP

Node OpenNLP - (OpenNLP 1.6.0)

OpenNLP Wrapper For Node.js

Node-OpenNLP is depended on Node-Java. Please take make sure your environment is properly configured to run Node-Java. Click here to learn more about Node-Java.

Installation

 npm install opennlp --save

Node-OpenNLP comes with Apache OpenNLP 1.6.0 along with the following trained 1.5 series models:

• en-chunker.bin
• en-ner-person.bin
• en-pos-maxent.bin
• en-sent.bin
• en-token.bin

More trained models can be found here: http://opennlp.sourceforge.net/models-1.5

Sentence Detector

The OpenNLP Sentence Detector can detect that a punctuation character marks the end of a sentence or not. In this sense a sentence is defined as the longest white space trimmed character sequence between two punctuation marks.

var openNLP = require("opennlp");
var sentence = 'Pierre Vinken , 61 years old , will join the board as a nonexecutive director Nov. 29 .';
var sentenceDetector = new openNLP().sentenceDetector;
sentenceDetector.sentDetect(sentence, function(err, results) {
  /// To get probabilities
    sentenceDetector.probs(function(error,probability){
      console.log(error,probability)
    })
	console.log(results)
});

Configurations

The following default configurations can be overrided during initialization.

var openNLP = require("opennlp");
var opennlp = new openNLP({
    models : {
        doccat:__dirname + '/models/en-doccat.bin',
        posTagger: __dirname + '/models/en-pos-maxent.bin',
        tokenizer: __dirname + '/models/en-token.bin',
        nameFinder: __dirname + '/models/en-ner-person.bin',
        sentenceDetector: __dirname + '/models/en-sent.bin',
        chunker: __dirname + '/models/en-chunker.bin'
    },
    openNLP = {
        jar: __dirname + "/lib/opennlp-tools-1.6.0.jar"
    }
});

Tokenizer

The OpenNLP Tokenizers segment an input character sequence into tokens. Tokens are usually words, punctuation, numbers, etc.

var openNLP = require("opennlp");
var sentence = 'Pierre Vinken , 61 years old , will join the board as a nonexecutive director Nov. 29 .';
var tokenizer = new openNLP().tokenizer;
tokenizer.tokenize(sentence, function(err, results) {
    console.log(err, results);
    tokenizer.getTokenProbabilities(function(error, response) {
            console.log(error, response
            });
    });
})

Name Finder

The Name Finder can detect named entities and numbers in text. To be able to detect entities the Name Finder needs a model. The model is dependent on the language and entity type it was trained for.

var openNLP = require("opennlp");
var sentence = 'Pierre Vinken , 61 years old , will join the board as a nonexecutive director Nov. 29 .';
var nameFinder = new openNLP().nameFinder;
nameFinder.find(sentence, function(err, tokens_arr) {
    console.log(error, response)
    nameFinder.probs(function(error, response) {
        console.log(error, response)
    });
});

Document Categorizer

The OpenNLP Document Categorizer can classify text into pre-defined categories. It is based on maximum entropy framework.

To use the document categorizer you need to train a model first. The default trained model that is included is for testing purposes only.

var openNLP = require("opennlp");
var doccat = new openNLP().doccat;
doccat.categorize("I enjoyed watching Rocky", function(err, list) {
    doccat.getAllResults(list, function(err, category) {
    });
    doccat.getBestCategory(list, function(err, category) {
    });
});
doccat.scoreMap("I enjoyed watching Rocky", function(err, category) {
});
doccat.sortedScoreMap("I enjoyed watching Rocky", function(err, category) {
});
doccat.getCategory(1, function(err, category) {
});
doccat.getIndex('Happy', function(err, index) {
});

Part-of-Speech Tagger

The Part of Speech Tagger marks tokens with their corresponding word type based on the token itself and the context of the token. A token might have multiple pos tags depending on the token and the context. The OpenNLP POS Tagger uses a probability model to predict the correct pos tag out of the tag set.

var openNLP = require("opennlp");
var posTagger = new openNLP().posTagger;
var sentence = 'Pierre Vinken , 61 years old , will join the board as a nonexecutive director Nov. 29 .';
posTagger.tag(sentence, function(err, tokens_arr) {
    console.log(err, tokens_arr)
});
posTagger.topKSequences(sentence, function(error, tagger) {
    console.log(tagger.getScore())
    console.log(tagger.getProbs())
    console.log(tagger.getOutcomes())
});

Chunker

Text chunking consists of dividing a text in syntactically correlated parts of words, like noun groups, verb groups, but does not specify their internal structure, nor their role in the main sentence.

var openNLP = require("opennlp");
var posTagger = new openNLP().posTagger;
var sentence = 'Pierre Vinken , 61 years old , will join the board as a nonexecutive director Nov. 29 .';
var chunker = new openNLP().chunker;
posTagger.tag(sentence, function(err, tokens_arr) {
    chunker.topKSequences(sentence, tokens_arr, function(err, tokens_arr) {
      console.log(err, tokens_arr)
    });
    chunker.chunk(sentence, tokens_arr, function(err, tokens_arr) {
        chunker.probs(function(error, prob) {

        });
    });
});