https://github.com/undertheseanlp/ner

Vietnamese Named Entity Recognition
https://github.com/undertheseanlp/ner

named-entity-recognition nlp

Last synced: 4 days ago
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Vietnamese Named Entity Recognition

• Host: GitHub
• URL: https://github.com/undertheseanlp/ner
• Owner: undertheseanlp
• Created: 2017-05-26T04:39:06.000Z (over 7 years ago)
• Default Branch: master
• Last Pushed: 2022-12-08T00:58:18.000Z (almost 2 years ago)
• Last Synced: 2023-02-28T15:46:58.908Z (over 1 year ago)
• Topics: named-entity-recognition, nlp
• Language: Python
• Homepage:
• Size: 105 MB
• Stars: 44
• Watchers: 4
• Forks: 15
• Open Issues: 8
• Metadata Files:
  • Readme: README.en.md

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README

        
# Vietnamese Named Entity Recognition ![](https://img.shields.io/badge/F1-88.6%25-red.svg)

[[English](README.en.md)] [[Vietnamese](README.vi.md)]

This repository contains starter code for training and evaluating machine learning models in *Vietnamese Named Entity Recognition* problem. It is a part of [underthesea](https://github.com/magizbox/underthesea) project. The code gives an end-to-end working example for reading datasets, training machine learning models, and evaluating performance of the models. It can easily be extended to train your own custom-defined models. 

## Table of contents

* [1. Installation](#1-installation)

  * [1.1 Requirements](#11-requirements)

  * [1.2 Download and Setup Environment](#12-download-and-setup-environment)

* [2. Usage](#2-usage)

  * [2.1 Using a pretrained model](#21-using-a-pretrained-model)

  * [2.2 Train a new dataset](#22-train-a-new-dataset)

  * [2.3 Sharing a model](#23-sharing-a-model)

* [3. References](#3-references)

## 1. Installation

### 1.1 Requirements

This code is writen in python. The dependencies are:

* `Operating Systems: Linux (Ubuntu, CentOS), Mac`

* `Python 3.6`

* `Anaconda`

Python Packages

* `underthesea==1.1.7`

* `languageflow==1.1.7`

### 1.2 Download and Setup Environment

Clone project using git

```

$ git clone https://github.com/undertheseanlp/ner.git

```

Create environment and install requirements

```

$ cd ner

$ conda create -n uts.ner python=3.5

$ pip install -r requirements.txt

```

## 2. Usage

### 2.1 Using a pretrained model

```

cd ner

$ source activate ner

$ python ner.py -fin tmp/input.txt -fout tmp/output.txt

```

### 2.2 Train a new dataset

Prepare a new dataset

Train and test

```

$ cd ner

$ source activate ner

$ python train.py

  --train data/vlsp2018/corpus/train.txt

```

### 2.3 Sharing a model

To be updated

## 3. References

To be updated

Last update: 07/2018