ezs-teeftfr

3.1.2 • Public • Published

Teeft adapted to French language

This package cannot be used alone. ezs has to be installed

Usage

import ezs from 'ezs';
import teeftfr from 'ezs-teeftfr';
 
ezs.use(teeftfr);
 
process.stdin
    .pipe(ezs('STATEMENT_NAME', { STATEMENT_PARAMETERS })
    .pipe(process.stdout);

Flow

The sequence of statements is determined by the structure of the expected input.

[ "/path/to/a/directory/of/documents" ] ->
 
[ListFiles]
pattern = *.txt
 
--> [ "/path1", "path2", ... ] -->
 
[GetFilesContent]
 
--> [ { path, content }, ... ] -->
 
[TEEFTSentenceTokenize]
 
--> [ { path, sentences: [ "sentence", ... ] }, ... ] -->
 
[TEEFTTokenize]
 
--> [ { path, sentences: [ ["token", ... ], ...] }, ... ] -->
 
[TEEFTNaturalTag]
 
--> [  { path, sentences: [ [
  {
    token: "token",
    tag: [ "tag", ...]
  }, ...
 ], ... ] }, ... ]
 
 
[TEEFTExtractTerms]
nounTag = NOM
adjTag = ADJ
 
--> [  { path, terms:  [
  {
    term: "monoterm",
    tag: [ "tag", ...],
    frequency,
    length
  },
  {
    term: "multiterm",
    frequency,
    length
  }, ...
 ] }, ... ]
 
[TEEFTFilterTags]
tags = NOM
tags = ADJ
 
--> [  { path, terms:  [
  {
    term: "monoterm",
    tag: [ "tag", ...],
    frequency,
    length
  },
  {
    term: "multiterm",
    frequency,
    length
  }, ...
 ] }, ... ]
 
[TEEFTStopWords]
 
--> [  { path, terms:  [
  {
    term: "monoterm",
    tag: [ "tag", ...],
    frequency,
    length
  },
  {
    term: "multiterm",
    frequency,
    length
  }, ...
 ] }, ... ]
 
[TEEFTSumUpFrequencies]
 
--> [  { path, terms:  [
  {
    term: "monoterm",
    tag: [ "tag", ...],
    frequency,
    length
  },
  {
    term: "multiterm",
    frequency,
    length
  }, ...
 ] }, ... ]
 
[TEEFTSpecificity]
sort = true
 
--> [  { path, terms:  [
  {
    term: "monoterm",
    tag: [ "tag", ...],
    frequency,
    length,
    specificity,
  },
  {
    term: "multiterm",
    frequency,
    length,
    specificity
  }, ...
 ] }, ... ]
 
[TEEFTFilterMonoFreq]
 
--> [  { path, terms:  [
  {
    term: "monoterm",
    tag: [ "tag", ...],
    frequency,
    length,
    specificity,
  },
  {
    term: "multiterm",
    frequency,
    length,
    specificity
  }, ...
 ] }, ... ]
 
[TEEFTFilterMultiSpec]
 
--> [  { path, terms:  [
  {
    term: "monoterm",
    tag: [ "tag", ...],
    frequency,
    length,
    specificity,
  },
  {
    term: "multiterm",
    frequency,
    length,
    specificity
  }, ...
 ] }, ... ]
 
[JSONString]
wrap = true
indent = true

Example

To use the example examples/teeftfr.ezs, you have to

  • install ezs
  • install ezs-teeftr
  • install ezs-basics
  • run the script

That is to say:

npm i ezs
npm i ezs-teeftfr
npm i ezs-basics
echo examples/data/fr-articles | npx ezs ./examples/teeftfr.ezs

You can even use jq to beautify the JSON in the output.

Statements

Table of Contents

TEEFTExtractTerms

Take an array of objects { path, sentences: [token, tag: ["tag"]]} Regroup multi-terms when possible (noun + noun, adjective + noun, etc.), and computes statistics (frequency, etc.).

Parameters

  • data Stream array of documents containing sentences of tagged tokens
  • feed Array<Objects> same as data, with term replacing token, length, and frequency
  • nounTag string noun tag (optional, default 'NOM')
  • adjTag string adjective tag (optional, default 'ADJ')

Examples

[{
   path: '/path/1',
   sentences:
   [[
     { token: 'elle', tag: ['PRO:per'] },
     { token: 'semble', tag: ['VER'] },
     { token: 'se', tag: ['PRO:per'] },
     { token: 'nourrir', tag: ['VER'] },
     {
       token: 'essentiellement',
       tag: ['ADV'],
     },
     { token: 'de', tag: ['PRE', 'ART:def'] },
     { token: 'plancton', tag: ['NOM'] },
     { token: 'frais', tag: ['ADJ'] },
     { token: 'et', tag: ['CON'] },
     { token: 'de', tag: ['PRE', 'ART:def'] },
     { token: 'hotdog', tag: ['UNK'] }
   ]]
}]

TEEFTFilterMonoFreq

Filter the data, keeping only multiterms and frequent monoterms.

Parameters

  • data Stream
  • feed Array<Object>
  • multiLimit Number threshold for being a multiterm (in tokens number) (optional, default 2)
  • minFrequency Number minimal frequency to be taken as a frequent term (optional, default 7)

TEEFTFilterMultiSpec

Filter multiterms to keep only multiterms which specificity is higher than multiterms' average specificity.

Parameters

  • data any
  • feed any

TEEFTFilterTags

Filter the text in input, by keeping only adjectives and names

Parameters

GetFilesContent

Take an array of file paths as input, and returns a list of objects containing the path, and the content of each file.

ListFiles

Take an array of directory paths as input, a pattern, and returns a list of file paths matching the pattern in the directories from the input.

Parameters

  • pattern String pattern for files (ex: "*.txt") (optional, default "*")

natural-tag

POS Tagger from natural

French pos tagging using natural (and LEFFF resources)

Take an array of documents (objects: { path, sentences: [[]] })

Yield an array of documents (objects: { path, sentences: [ [{ token: "token", tag: [ "tag", ... ] }, ...] ] })

Examples

[{
     path: "/path/1",
     sentences: [{ "token": "dans",      "tag": ["prep"] },
                 { "token": "le",        "tag": ["det"]  },
                 { "token": "cadre",     "tag": ["nc"] },
                 { "token": "du",        "tag": ["det"] },
                 { "token": "programme", "tag": ["nc"] }
                 },
     ]
 }]

profile

Profile the time a statement takes to execute.

You have to place one to initialize, and a second to display the time it takes.

Parameters

  • data any
  • feed any

TEEFTSentenceTokenize

Segment the data into an array of documents (objects { path, content }).

Yield an array of documents (objects { path, sentences: []})

TEEFTSpecificity

Take documents (with a path, an array of terms, each term being an object { term, frequency, length[, tag] })

Process objects containing frequency, add a specificity to each object, and remove all object with a specificity below average specificity (except when filter is false).

Can also sort the objects according to their specificity, when sort is true.

Parameters

  • data any
  • feed any
  • weightedDictionary string name of the weigthed dictionary (optional, default "Ress_Frantext")
  • filter Boolean filter below average specificity (optional, default true)
  • sort Boolean sort objects according to their specificity (optional, default false)

TEEFTStopWords

Filter the text in input, by removing stopwords in token

Parameters

  • data Stream
  • feed Array<Object>
  • stopwords string name of the stopwords file to use (optional, default 'StopwFrench')

TEEFTSumUpFrequencies

Sums up the frequencies of identical lemmas from different chunks.

Parameters

ToLowerCase

Transform strings to lower case.

Parameters

  • data any
  • feed any
  • path Array<string> path to the property to modify

TEEFTTokenize

Extract tokens from an array of documents (objects { path, sentences: [] }).

Yields an array of documents (objects: { path, sentences: [[]] })

Warning: results are surprising on uppercase sentences

Install

npm i ezs-teeftfr

DownloadsWeekly Downloads

3

Version

3.1.2

License

MIT

Unpacked Size

33 MB

Total Files

47

Last publish

Collaborators

  • parmentf