# nlptoolkit-dictionary
> Turkish Dictionary
Latest version **1.0.16** (published 2026-05-01) · ISC license · 0 weekly downloads
## Install
```sh
npm install nlptoolkit-dictionary
pnpm add nlptoolkit-dictionary
yarn add nlptoolkit-dictionary
bun add nlptoolkit-dictionary
```
## Health
**Score 55/100 (C)** — status: active.
Positive: has types; no vulnerabilities; high quality score.
Warnings: low downloads; no esm support.
## Facts
| | |
|---|---|
| Version | 1.0.16 |
| Published | 2026-05-01 |
| First published | 2021-11-13 |
| Weekly downloads | 0 |
| License | ISC |
| TypeScript types | bundled |
| Module format | CommonJS |
| Dependencies | 2 |
| Unpacked size | 5.7 MB |
| Known vulnerabilities | 0 |
| Install scripts | no |
| GitHub stars | 2 |
| Author | Olcay Taner Yıldız |
| Maintainers | olcaytaner |
## Links
- npm: https://www.npmjs.com/package/nlptoolkit-dictionary
- Repository: https://github.com/StarlangSoftware/Dictionary-Js
- Homepage: https://github.com/StarlangSoftware/Dictionary-Js#readme
- Issues: https://github.com/StarlangSoftware/Dictionary-Js/issues
- npm.io page: https://npm.io/package/nlptoolkit-dictionary
## Dependencies (2)
- [nlptoolkit-math](https://npm.io/package/nlptoolkit-math.md) ^1.0.7
- [nlptoolkit-util](https://npm.io/package/nlptoolkit-util.md) ^1.0.12
## Recent versions
- 1.0.16 (latest) — 2026-05-01
- 1.0.15 — 2026-04-27
- 1.0.14 — 2026-02-15
- 1.0.13 — 2026-02-14
- 1.0.12 — 2024-08-25
- 1.0.11 — 2022-11-24
- 1.0.10 — 2022-11-22
- 1.0.9 — 2022-11-21
- 1.0.8 — 2022-09-05
- 1.0.7 — 2022-09-03
- 1.0.6 — 2022-08-24
- 1.0.5 — 2022-08-04
- 1.0.4 — 2022-04-21
- 1.0.3 — 2022-02-11
- 1.0.2 — 2021-12-03
- … 2 more at https://npm.io/package/nlptoolkit-dictionary/versions
## README
Turkish Dictionary
============
This resource is a dictionary of Modern Turkish, comprised of the definitions of over 50.000 individual entries. Each entry is matched with its corresponding synset (set of synonymous words and expressions) in the Turkish WordNet, KeNet.
The bare-forms in the lexicon consists of nouns, adjectives, verbs, adverbs, shortcuts, etc. Each bare-form appears the same in the lexicon except verbs. Since the bare-forms of the verbs in Turkish do not have the infinitive affix ‘mAk’, our lexicon includes all verbs without the infinitive affix. The bare-forms with diacritics are included in two forms, with and without diacritics. For example, noun ‘rüzgar’ appear both as ‘rüzgar’ and ‘rüzgâr’.
Special markers are included as bare-forms such as doc, s, etc.
Some compound words are included in their affixed form. For instance, ‘acemlalesi’ appears as it is, but not as ‘acemlale’.
Foreign words, especially proper noun foreign words, are included, so that the system can easily recognize them as proper nouns. For instance, the words ‘abbott’, ‘abbigail’ are example foreign proper nouns. Including foreign proper nouns, there are 19,000 proper nouns in our lexicon.
From derivational suffixes, we only include words which has taken -lI, -sIz, -CI, -lIk, and -CIlIk derivational affixes. For example, the bare-forms ‘abacı’, ‘abdallık’, ‘abdestli’ and ‘abdestlilik’, are included, since they have taken one or more derivational affixes listed above.
Each bare-form has a set of attributes. For instance, ‘abacı’ is a noun, therefore, it includes CL_ISIM attribute. Similarly, ‘abdestli’ is an adjective, which includes IS_ADJ attribute. If the bare-form has homonyms with different part of speech tags, all corresponding attributes are included.
|Name|Purpose|
|---|---|
|CL ISIM, CL FIIL, IS_OA|Part of speech tag(s)|
|IS_DUP|Part of a duplicate form|
|IS_KIS|Abbreviation, which does not obey vowel harmony while taking suffixes.|
|IS_UU, IS_UUU|Does not obey vowel harmony while taking suffixes.|
|IS_BILES|A portmanteau word in affixed form, such as ‘adamotu’|
|IS_B_SI|A portmanteau word ending with ‘sı’, such as ‘acemlalesi’|
|IS_CA|Already in a plural form, therefore can not take plural suffixes such as ‘ler’ or ‘lar’.|
|IS_ST|The second consonant undergoes a resyllabification.|
|IS_UD, IS_UDD, F_UD|Includes vowel epenthesis.|
|IS_KG|Ends with a ‘k’, and when it is followed by a vowel-initial suffix, the final ‘k’ is replaced with a ‘g’.|
|IS_SD, IS_SDD, F_SD|Final consonant gets devoiced during vowel-initial suffixation.|
|F GUD, F_GUDO|The verb bare-form includes vowel reduction.|
|F1P1, F1P1-NO-REF|A verb, and depending on this attribute, the verb can (or can not) take causative suffix, factitive suffix, passive suffix etc.|
Simple Web Interface
============
[Turkish Dictionary Search Link 1](http://104.247.163.162/nlptoolkit/turkish-dictionary.html) [Turkish Dictionary Search Link 2](https://starlangsoftware.github.io/nlptoolkit-web-simple/turkish-dictionary.html)
[Turkish MorphoLex Search Link 1](http://104.247.163.162/nlptoolkit/turkish-morphological-lexicon.html) [Turkish MorphoLex Search Link 2](https://starlangsoftware.github.io/nlptoolkit-web-simple/turkish-morphological-lexicon.html)
Video Lectures
============
[
](https://youtu.be/10iAqbfsA2A)[
](https://youtu.be/C-_TZDkFwzQ)
For Developers
============
You can also see [Python](https://github.com/starlangsoftware/Dictionary-Py), [Cython](https://github.com/starlangsoftware/Dictionary-Cy),
[C++](https://github.com/starlangsoftware/Dictionary-CPP), [C](https://github.com/starlangsoftware/Dictionary-C), [Swift](https://github.com/starlangsoftware/Dictionary-Swift),
[Java](https://github.com/starlangsoftware/Dictionary), [Php](https://github.com/starlangsoftware/Dictionary-Php), or [C#](https://github.com/starlangsoftware/Dictionary-CS) repository.
## Requirements
* [Node.js 14 or higher](#Node.js)
* [Git](#git)
### Node.js
To check if you have a compatible version of Node.js installed, use the following command:
node -v
You can find the latest version of Node.js [here](https://nodejs.org/en/download/).
### Git
Install the [latest version of Git](https://git-scm.com/book/en/v2/Getting-Started-Installing-Git).
## Npm Install
npm install nlptoolkit-dictionary
## Download Code
In order to work on code, create a fork from GitHub page.
Use Git for cloning the code to your local or below line for Ubuntu:
git clone
A directory called util will be created. Or you can use below link for exploring the code:
git clone https://github.com/starlangsoftware/dictionary-js.git
## Open project with Webstorm IDE
Steps for opening the cloned project:
* Start IDE
* Select **File | Open** from main menu
* Choose `Dictionary-Js` file
* Select open as project option
* Couple of seconds, dependencies will be downloaded.
Detailed Description
============
+ [TxtDictionary](#txtdictionary)
+ [TxtWord](#txtword)
+ [SyllableList](#syllablelist)
## TxtDictionary
Dictionary is used in order to load Turkish dictionary or a domain specific dictionary. In addition, misspelled words and the true forms of the misspelled words can also be loaded.
To load the Turkish dictionary and the misspelled words dictionary,
a = TxtDictionary()
To load the domain specific dictionary and the misspelled words dictionary,
constructor(comparator: WordComparator = WordComparator.TURKISH,
fileName: string = "turkish_dictionary.txt",
misspelledFileName: string = "turkish_misspellings.txt")
And to see if the dictionary involves a specific word, Word getWord is used.
getWord(nameOrIndex: any): Word
## TxtWord
The word features:
To see whether the TxtWord class of the dictionary is a noun or not,
isNominal(): boolean
To see whether it is an adjective,
isAdjective(): boolean
To see whether it is a portmanteau word,
isPortmanteau(): boolean
To see whether it obeys vowel harmony,
notObeysVowelHarmonyDuringAgglutination(): boolean
And, to see whether it softens when it get affixes, the following is used.
rootSoftenDuringSuffixation(): boolean
## SyllableList
To syllabify the word, SyllableList class is used.
constructor(word: string)
# Cite
@inproceedings{yildiz-etal-2019-open,
title = "An Open, Extendible, and Fast {T}urkish Morphological Analyzer",
author = {Y{\i}ld{\i}z, Olcay Taner and
Avar, Beg{\"u}m and
Ercan, G{\"o}khan},
booktitle = "Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2019)",
month = sep,
year = "2019",
address = "Varna, Bulgaria",
publisher = "INCOMA Ltd.",
url = "https://www.aclweb.org/anthology/R19-1156",
doi = "10.26615/978-954-452-056-4_156",
pages = "1364--1372",
}
For Contibutors
============
### package.json file
1. main and types are important when this package will be imported.
```
"main": "dist/index.js",
"types": "dist/index.d.ts",
```
2. Dependencies should be maximum (not only direct but also indirect references should also be given), everything directly in the code should be given here.
```
"dependencies": {
"nlptoolkit-corpus": "^1.0.12",
"nlptoolkit-dictionary": "^1.0.14",
"nlptoolkit-morphologicalanalysis": "^1.0.19",
"nlptoolkit-xmlparser": "^1.0.7"
}
```
### tsconfig.json file
1. Compiler flags currently includes nodeNext for importing.
```
"compilerOptions": {
"outDir": "dist",
"module": "nodeNext",
"sourceMap": true,
"noImplicitAny": true,
"removeComments": false,
"declaration": true,
},
```
2. tests, node_modules and dist should be excluded.
```
"exclude": [
"tests",
"node_modules",
"dist"
]
```
### index.ts file
1. Should include all ts classes.
```
export * from "./CategoryType"
export * from "./InterlingualDependencyType"
export * from "./InterlingualRelation"
export * from "./Literal"
```
### Data files
1. Add data files to the project folder. Subprojects should include all data files of the parent projects.
### Javascript files
1. Classes should be defined as exported.
```
export class JCN extends ICSimilarity{
```
2. Do not forget to comment each function.
```
/**
* Computes JCN wordnet similarity metric between two synsets.
* @param synSet1 First synset
* @param synSet2 Second synset
* @return JCN wordnet similarity metric between two synsets
*/
computeSimilarity(synSet1: SynSet, synSet2: SynSet): number {
```
3. Function names should follow caml case.
```
setSynSetId(synSetId: string){
```
4. Write getter and setter methods.
```
getRelation(index: number): Relation{
setName(name: string){
```
5. Use standard javascript test style.
```
describe('SimilarityPathTest', function() {
describe('SimilarityPathTest', function() {
it('testComputeSimilarity', function() {
let turkish = new WordNet();
let similarityPath = new SimilarityPath(turkish);
assert.strictEqual(32.0, similarityPath.computeSimilarity(turkish.getSynSetWithId("TUR10-0656390"), turkish.getSynSetWithId("TUR10-0600460")));
assert.strictEqual(13.0, similarityPath.computeSimilarity(turkish.getSynSetWithId("TUR10-0412120"), turkish.getSynSetWithId("TUR10-0755370")));
assert.strictEqual(13.0, similarityPath.computeSimilarity(turkish.getSynSetWithId("TUR10-0195110"), turkish.getSynSetWithId("TUR10-0822980")));
});
});
});
```
6. Enumerated types should be declared with enum.
```
export enum CategoryType {
MATHEMATICS, SPORT, MUSIC, SLANG, BOTANIC,
PLURAL, MARINE, HISTORY, THEOLOGY, ZOOLOGY,
METAPHOR, PSYCHOLOGY, ASTRONOMY, GEOGRAPHY, GRAMMAR,
MILITARY, PHYSICS, PHILOSOPHY, MEDICAL, THEATER,
ECONOMY, LAW, ANATOMY, GEOMETRY, BUSINESS,
PEDAGOGY, TECHNOLOGY, LOGIC, LITERATURE, CINEMA,
TELEVISION, ARCHITECTURE, TECHNICAL, SOCIOLOGY, BIOLOGY,
CHEMISTRY, GEOLOGY, INFORMATICS, PHYSIOLOGY, METEOROLOGY,
MINERALOGY
}
```
7. If there are multiple constructors for a class, define them as constructor1, constructor2, ..., then from the original constructor call these methods.
```
constructor1(symbol: any){
constructor2(symbol: any, multipleFile: MultipleFile) {
constructor(symbol: any, multipleFile: MultipleFile = undefined) {
if (multipleFile == undefined){
this.constructor1(symbol);
} else {
this.constructor2(symbol, multipleFile);
}
}
```
8. Importing should be done via import method with referencing the node-modules.
```
import {Corpus} from "nlptoolkit-corpus/dist/Corpus";
import {Sentence} from "nlptoolkit-corpus/dist/Sentence";
```
9. Use xmlparser package for parsing xml files.
```
var doc = new XmlDocument("test.xml")
doc.parse()
let root = doc.getFirstChild()
let firstChild = root.getFirstChild()
```
---
_Source: https://npm.io/package/nlptoolkit-dictionary · Machine-readable twin of the npm.io package page. Health data is recomputed on every publish._