node-opennlp

NOTE: This project is a fork of Node-OpenNLP by @mbejda. The fork was created to fix version related errors and to migrate it to modern ECMAScript syntax.

OpenNLP 1.6.0 Wrapper For Node.js

node-opennlp relies on java npm module, and interfaces with Apache-OpenNLP using that.

$3

``bash
npm install node-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

$3

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.

`Javascript
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)
});
`

$3


The following default configurations can be overrided during initialization.
`Javascript
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"
}
});

`

$3

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

`Javascript
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
});
});
})
`

$3

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.

`Javascript
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(err, tokens_arr)
nameFinder.probs(function(error, response) {
console.log(error, response)
});
});
`




$3

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.
`Javascript
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) {
});
`

$3

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.

` Javascript
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())
});
`


$3

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.

`Javascript
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) {

});
});
});
``