SAPPHIRE is a simple monolingual phrase aligner based on word embeddings.

SAPPHIRE depends only on a pre-trained word embedding. Therefore, it is easily transferable to specific domains and different languages.
This library is designed for a pre-trained model of fastText. But it is easy to replace the model.

• Python 3.6 or newer
• NumPy & SciPy
• fasttext

1. Install requirements
   After cloning this repository, go to the root directory and install requirements.

$ pip install -r requirements.txt

2. Install SAPPHIRE
   Installation with develop option allows you to change the parameters and add scripts for other word representations.

$ python setup.py develop

3. Download the pre-trained model of fastText (or prepare your model of fastText) and move it to model directory.

$ curl -O https://dl.fbaipublicfiles.com/fasttext/vectors-english/wiki-news-300d-1M-subword.bin.zip  
$ unzip wiki-news-300d-1M-subword.bin.zip
$ mkdir model
$ mv wiki-news-300d-1M-subword.bin model/

$ python run_sapphire.py

To stop SAPPHIRE, enter exit when inputting a sentence.

>>> from sapphire import Sapphire
>>> aligner = Sapphire()

After preparing a tokenized sentence pair (tokenized_sentence_a: list and tokenized_sentence_b: list),

>>> result = aligner.align(tokenized_sentence_a, tokenized_sentence_b)
>>> alignment = result.top_alignment[0][0]
>>> print(alignment)
1,2,3-2,3 8,9-5,6 13-8 27-9

Output format: 1-indexed alignment