# nlptoolkit-namedentityrecognition

> NER Corpus Processing Library

Latest version **1.0.3** (published 2026-02-15) · ISC license · 0 weekly downloads

## Install

```sh
npm install nlptoolkit-namedentityrecognition
pnpm add nlptoolkit-namedentityrecognition
yarn add nlptoolkit-namedentityrecognition
bun add nlptoolkit-namedentityrecognition
```

## Health

**Score 55/100 (C)** — status: stable.

Positive: has types; no vulnerabilities; high quality score.

Warnings: low downloads; no esm support.

## Facts

| | |
|---|---|
| Version | 1.0.3 |
| Published | 2026-02-15 |
| First published | 2021-11-26 |
| Weekly downloads | 0 |
| License | ISC |
| TypeScript types | bundled |
| Module format | CommonJS |
| Dependencies | 3 |
| Unpacked size | 4.8 MB |
| Known vulnerabilities | 0 |
| Install scripts | no |
| GitHub stars | 0 |
| Author | Olcay Taner Yıldız |
| Maintainers | olcaytaner |

## Links

- npm: https://www.npmjs.com/package/nlptoolkit-namedentityrecognition
- Repository: https://github.com/StarlangSoftware/TurkishNamedEntityRecognition-Js
- Homepage: https://github.com/StarlangSoftware/TurkishNamedEntityRecognition-Js#readme
- Issues: https://github.com/StarlangSoftware/TurkishNamedEntityRecognition-Js/issues
- npm.io page: https://npm.io/package/nlptoolkit-namedentityrecognition

## Dependencies (3)

- [nlptoolkit-corpus](https://npm.io/package/nlptoolkit-corpus.md) ^1.0.12
- [nlptoolkit-dictionary](https://npm.io/package/nlptoolkit-dictionary.md) ^1.0.14
- [nlptoolkit-datastructure](https://npm.io/package/nlptoolkit-datastructure.md) ^1.0.9

## Recent versions

- 1.0.3 (latest) — 2026-02-15
- 1.0.2 — 2026-02-14
- 1.0.1 — 2022-11-21
- 1.0.0 — 2021-11-26

## README

Named Entity Recognition Task
============

In named entity recognition, one tries to find the strings within a text that correspond to proper names (excluding TIME and MONEY) and classify the type of entity denoted by these strings. The problem is difficult partly due to the ambiguity in sentence segmentation; one needs to extract which words belong to a named entity, and which not. Another difficulty occurs when some word may be used as a name of either a person, an organization or a location. For example, Deniz may be used as the name of a person, or - within a compound - it can refer to a location Marmara Denizi 'Marmara Sea', or an organization Deniz Taşımacılık 'Deniz Transportation'.

The standard approach for NER is a word-by-word classification, where the classifier is trained to label the words in the text with tags that indicate the presence of particular kinds of named entities. After giving the class labels (named entity tags) to our training data, the next step is to select a group of features to discriminate different named entities for each input word.

[<sub>ORG</sub> Türk Hava Yolları] bu [<sub>TIME</sub> Pazartesi'den] itibaren [<sub>LOC</sub> İstanbul] [<sub>LOC</sub> Ankara] hattı için indirimli satışlarını [<sub>MONEY</sub> 90 TL'den] başlatacağını açıkladı.

[<sub>ORG</sub> Turkish Airlines] announced that from this [<sub>TIME</sub> Monday] on it will start its discounted fares of [<sub>MONEY</sub> 90TL] for [<sub>LOC</sub> İstanbul] [<sub>LOC</sub> Ankara] route.

See the Table below for typical generic named entity types.

|Tag|Sample Categories|
|---|---|
|PERSON|people, characters|
|ORGANIZATION|companies, teams|
|LOCATION|regions, mountains, seas|
|TIME|time expressions|
|MONEY|monetarial expressions|

Video Lectures
============

[<img src="https://github.com/StarlangSoftware/TurkishNamedEntityRecognition/blob/master/video.jpg" width="50%">](https://youtu.be/tuuc5W5oNPw)

For Developers
============

You can also see [Java](https://github.com/starlangsoftware/TurkishNamedEntityRecognition), [Python](https://github.com/starlangsoftware/TurkishNamedEntityRecognition-Py), [Cython](https://github.com/starlangsoftware/TurkishNamedEntityRecognition-Cy), 
[Swift](https://github.com/starlangsoftware/TurkishNamedEntityRecognition-Swift), [C](https://github.com/starlangsoftware/TurkishNamedEntityRecognition-C), [C++](https://github.com/starlangsoftware/TurkishNamedEntityRecognition-CPP), 
or [C#](https://github.com/starlangsoftware/TurkishNamedEntityRecognition-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-namedentityrecognition
	
## 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 <your-fork-git-link>

A directory called util will be created. Or you can use below link for exploring the code:

	git clone https://github.com/starlangsoftware/namedentityrecognition-js.git

## Open project with Webstorm IDE

Steps for opening the cloned project:

* Start IDE
* Select **File | Open** from main menu
* Choose `Namedentityrecognition-Js` file
* Select open as project option
* Couple of seconds, dependencies will be downloaded. 

Detailed Description
============

+ [Gazetteer](#gazetteer)

## Gazetteer

Bir Gazetter yüklemek için

	Gazetteer(name: string, fileName: string)

Hazır Gazetteerleri kullanmak için

	AutoNER()

Bir Gazetteer'de bir kelime var mı diye kontrol etmek için

	contains(word: string):boolean

# Cite

	@INPROCEEDINGS{8093439,
  	author={B. {Ertopçu} and A. B. {Kanburoğlu} and O. {Topsakal} and O. {Açıkgöz} and A. T. {Gürkan} and B. {Özenç} and İ. {Çam} and B. {Avar} and G. {Ercan} 	and O. T. {Yıldız}},
  	booktitle={2017 International Conference on Computer Science and Engineering (UBMK)}, 
  	title={A new approach for named entity recognition}, 
  	year={2017},
  	volume={},
  	number={},
  	pages={474-479},
  	doi={10.1109/UBMK.2017.8093439}}

---
_Source: https://npm.io/package/nlptoolkit-namedentityrecognition · Machine-readable twin of the npm.io package page. Health data is recomputed on every publish._