https://github.com/unfoldingword/wordmap

Multilingual Word Alignment Prediction
https://github.com/unfoldingword/wordmap

scripture-open-components wordmap

Last synced: about 2 months ago
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Multilingual Word Alignment Prediction

• Host: GitHub
• URL: https://github.com/unfoldingword/wordmap
• Owner: unfoldingWord
• Created: 2018-01-16T15:41:58.000Z (over 7 years ago)
• Default Branch: master
• Last Pushed: 2023-01-04T23:40:15.000Z (over 2 years ago)
• Last Synced: 2025-04-11T10:45:31.547Z (about 2 months ago)
• Topics: scripture-open-components, wordmap
• Language: TypeScript
• Homepage: https://wordmap.netlify.com
• Size: 2.01 MB
• Stars: 6
• Watchers: 9
• Forks: 1
• Open Issues: 20
• Metadata Files:
  • Readme: README.md

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README

        
# wordMAP

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[![npm version](https://badge.fury.io/js/wordmap.svg)](https://badge.fury.io/js/wordmap)

> Multi-Lingual Word Alignment Prediction

Word alignment prediction is the process of associating (mapping) words from some primary text with corresponding words in a secondary text. 

his tool uses statistical algorithms to determine which words or phrases in two texts are equivalent in meaning.

With wordMAP you can create amazing translation tools that:

* Ensure all terms and phrases in the primary text have a proper translation in the secondary text.

* Provide in-context vocabulary suggestions to the translator.

* Helps prevent inconsistencies in the translation.

* Pre-translates text.

## Installation

```

yarn add wordmap

```

## Usage

Here's a minimum setup example.

```

const map = new WordMAP();

map.appendAlignmentMemoryString("Tag", "day");

const source = "Guten Tag";

const target = "Good morning";

const suggestions = map.predict(source, target);

console.log(suggestions[0].toString());

// produces -> "0 [0|n:guten->n:good] [0|n:tag->n:morning]"

```

## Use Cases

* Aligning a primary text with a secondary text e.g. when generating word maps for gateway languages.

* Aligning a secondary text with a ternary text.

* Aligning a primary text to a ternary text (using the secondary as a proxy)

## The Need

Existing tools require large data sets, complex running environments, and are usually limited to running in a server environment.

We need a tool that:

* runs on the client with minimal configuration.

* works with existing web browser technology.

* integrates with translationCore and related tools.

* works without an Internet connection.

* does not have a minimum corpus size.

* requires minimal system resources.

## Learn more

Want to learn more? Read [WHITEPAPER.md](./WHITEPAPER.md).

## Development

When publishing to npm be sure to use the command `yarn deploy`.

This will publish the proper module structure to npm.