nlp-js-tools-french

    1.0.9 • Public • Published

    NLP Javascript tools for french language

    Tokenize, POS Tagger, lemmatizer and stemmer

    This package is partly based on the Snowball stemming algorythm and the javascript adaptation by Kasun Gajasinghe, University of Moratuwa

    This package offers 4 NLP tools in javascript for french language :

    • Tokenizing
    • POS Tagging
    • Lemmatizing
    • Stemming

    Install

    npm install nlp-js-tools-french
    

    Usage

    var NlpjsTFr = require('nlp-js-tools-french');
    

    Corpus to use

    var corpus = "Elle semble se nourrir essentiellement de plancton, et de hotdog.";
    

    Configs

    var config = {
        tagTypes: ['art', 'ver', 'nom'],
        strictness: false,
        minimumLength: 3,
        debug: true
    };
    

    New instance with specific corpus and configs

    var nlpToolsFr = new NlpjsTFr(corpus, config);
    

    These are the available methods, self-explanatory. Note: The sentence that is passed into the class earlier is automaticaly tokenized.

    var tokenizedWords = nlpToolsFr.tokenized;
    var posTaggedWords = nlpToolsFr.posTagger();
    var lemmatizedWords = nlpToolsFr.lemmatizer();
    var stemmedWords = nlpToolsFr.stemmer();
    var stemmedWord = nlpToolsFr.wordStemmer("aléatoirement");
    

    Attributes

    config

    Shows config

    tokenized

    ["semble", "nourrir", "de"]
    

    Methods return

    posTagger()

    [{
      "id": 1,
      "word": "semble",
      "pos": [
       "VER",
       "VER"
      ]
     },
     {
      "id": 2,
      "word": "nourrir",
      "pos": [
       "VER"
      ]
     },
     {
      "id": 3,
      "word": "de",
      "pos": [
       "NOM",
       "ART:def",
       "PRE"
      ]
     }]
    

    lemmatizer()

    [{
      "id": 1,
      "word": "semble",
      "lemma": "sembler"
     },
     {
      "id": 2,
      "word": "nourrir",
      "lemma": "nourrir"
     },
     {
      "id": 3,
      "word": "de",
      "lemma": "de"
     }]
    

    stemmer()

    [{
      "id": 1,
      "word": "semble",
      "stem": "sembl"
     },
     {
      "id": 3,
      "word": "nourrir",
      "stem": "nourr"
     },
     {
      "id": 5,
      "word": "de",
      "stem": "de"
    }]
    

    wordStemmer(word)

    {
        word: "aléatoirement",
        stem: "aléatoir"
    }
    

    Config

    Option Type Default Description
    tagTypes Array ["adj", "adv", "art", "con", "nom", "ono", "pre", "ver", "pro"] List of dictionnaries the package will look in, in case you only need verbs or nouns, both or whatever else. If a word does not belong to any type, it is tagged as "UNK".
    strictness Bool false If you set the strictness to true and try to POS Tag the word generalement, it will fail because the word is missine its accents. On the other hand, trying to POS Tag the word with the strictness set to false well return the types art, pre and nom because the word will match de in these dictionnaries.
    minimumLength Int 1 Algorythms will ignore words that are shorter than this parameter.
    debug Bool false Enable console debug

    Install

    npm i nlp-js-tools-french

    DownloadsWeekly Downloads

    32

    Version

    1.0.9

    License

    MIT

    Last publish

    Collaborators

    • avatar