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# Evaluating cross-lingual textual similarity on dictionary alignment
This repository contains the scripts to prepare the resources for the study as well as open source implementations of the methods.
## Requirements
- Python 3
- nltk
```python
import nltk
nltk.download('wordnet')
```
## Acquiring The Data
```bash
git clone https://github.com/yigitsever/Evaluating-Dictionary-Alignment.git && cd Evaluating-Dictionary-Alignment
./get_data.sh
```
This will create two directories; `dictionaries` and `wordnets`.
Linewise aligned definition files are in `wordnets/ready`.
## Acquiring The Embeddings
We use [VecMap](https://github.com/artetxem/vecmap) on [fastText](https://fasttext.cc/) embeddings.
You can skip this step if you are providing your own polylingual embeddings.
Otherwise;
* initialize and update the VecMap submodule;
```bash
git submodule init && git submodule update
```
* make sure `./get_data` is already run and `dictionaries` directory is present.
* run;
```bash
./get_embeddings.sh
```
Bear in mind that this will require around 30 GB free space.
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