https://github.com/bastienbot/nlp-js-tools-french

POS Tagger, lemmatizer and stemmer for french language in javascript
https://github.com/bastienbot/nlp-js-tools-french

lemmatization lemmatizer nlp postagging postgresql stemmer stemming tokenization tokenizer

Last synced: 2 months ago
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POS Tagger, lemmatizer and stemmer for french language in javascript

• Host: GitHub
• URL: https://github.com/bastienbot/nlp-js-tools-french
• Owner: bastienbot
• License: mit
• Created: 2017-04-21T13:15:33.000Z (over 7 years ago)
• Default Branch: master
• Last Pushed: 2017-09-13T13:58:49.000Z (about 7 years ago)
• Last Synced: 2024-08-06T03:09:40.654Z (3 months ago)
• Topics: lemmatization, lemmatizer, nlp, postagging, postgresql, stemmer, stemming, tokenization, tokenizer
• Language: JavaScript
• Homepage:
• Size: 1.04 MB
• Stars: 36
• Watchers: 4
• Forks: 8
• Open Issues: 1
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# NLP Javascript tools for french language

#### Tokenize, POS Tagger, lemmatizer and stemmer

This package is partly based on the [Snowball stemming algorythm](https://snowballstem.org/algorithms/french/stemmer.html) and the [javascript adaptation](http://snowball.tartarus.org/otherlangs/french_javascript.txt) 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 `dé` 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