react-native-mlkit-entity-extraction
v1.0.0
Published
text entity extraction; based on google mlkits
Downloads
6
Maintainers
Readme
| | MLKitEntityExtractor | | - | ------------ | | ⚡️ | Multiple Language Support over 10 languages supported (full list) | | 😎 | Lazy loaded. download models when needed | | 🔄 | Offline-first. no network required for using | | 📱 | Multiplatform. iOS, Android | | ⏱ | Fast. About TO Migrating to RN New Arch(JSI) | | 🔗 | Relational. Built on MLKit Translation foundation | | ⚠️ | Static typing Full-Support TypeScript |
Why MLKitEntityExtractor?
Most apps offer users very little interaction with text beyond the basic cut/copy/paste operations. Entity extraction improves the user experience inside your app by understanding text and allowing you to add helpful shortcuts based on context.
The Entity Extraction API allows you to recognize specific entities within static text and while you're typing. Once an entity is identified, you can easily enable different actions for the user based on the entity type. Supported entities included are:
| Entity | Example | | - | --------- | | Address| 350 third street, Cambridge MA | Date-Time| 2019/09/29, let's meet tomorrow at 6pm | Email address | [email protected] | Flight Number | (IATA flight codes only) LX37 | IBAN | CH52 0483 0000 0000 0000 9 | ISBN | (version 13 only) 978-1101904190 | Money/Currency (Arabic numerals only) | $12, 25 USD | Payment / Credit Cards| 4111 1111 1111 1111 | Phone Number| (555) 225-3556 12345 | Tracking Number (standardized international formats)|1Z204E380338943508 | URL| www.google.com https://en.wikipedia.org/wiki/Platypus
This API focuses on precision over recognition. Some instances of a particular entity might not be detected in favor of ensuring accuracy.
Installation
yarn add react-native-mlkit-entity-extraction
or
npm i --save react-native-mlkit-entity-extraction
! Android Special
// 31 is required !
compileSdkVersion = 31
targetSdkVersion = 31
Usage
Quick example: identify language type
import MLKitEntityExtraction from './MLKitEntityExtraction';
const text = "My flight is LX373, please pick me up at 8am tomorrow. You can look up at http://github.com";
MLKitEntityExtraction.isModelDownloaded('ENGLISH')
.then(v => {
if (v) {
//extrac it right now
MLKitEntityExtraction.annotate(
text,
'ENGLISH',
['TYPE_FLIGHT_NUMBER','TYPE_DATE_TIME','TYPE_URL']
).then(v => {
setExtractions(v);
}).catch(e => {
//something wrong
})
}else{
//download model
MLKitEntityExtraction
.downloadModel('ENGLISH')
.then(rs => {
//download success
}).catch(e => {
//something wrong
})
}
});
Remember !!! ✨ Always check model firstly ; Do not translate text if the model is not downloaded
use MLKitEntityExtraction.isModelDownloaded to check
Full Support Language
- ARABIC
- GERMAN
- ENGLISH
- SPANISH
- FRENCH
- ITALIAN
- JAPANESE
- KOREAN
- DUTCH
- POLISH
- PORTUGUESE
- RUSSIAN
- THAI
- TURKISH
- CHINESE
All Supported Entity Type
- ADDRESS
- DATE_TIME
- FLIGHT_NUMBER
- IBAN
- ISBN
- PAYMENT_CARD
- PHONE
- TRACKING_NUMBER
- URL
- MONEY
Author and license
WatermelonDB was created by @yaaliuzhipeng
react-native-mlkit-translate-text is available under the MIT license. See the LICENSE file for more info.