Update README.md

# absinth

Absinth is a graph based approach to word sense induction. Out system is based on Hyperlex (Véronis 2004) and made for SemEval-2013 Task 11 (Navigli, Vannella).

## Getting Started

Clone our system using git.

```

git clone https://gitlab.cl.uni-heidelberg.de/zimmermann/absinth/

```

### Prerequisites

Download the evaluator and dataset from the task page and place them in the appropriate folders. This repository already includes a version of this evaluator. For proper testing however, the official one should be used.

```

https://www.cs.york.ac.uk/semeval-2013/task11/index.php%3Fid=data.html

```

### Installing

A step by step series of examples that tell you have to get a development env running

Change to source directory.

```

$ cd absinth/src

```

Run setup.py.

```

python3 setup.py

```

Specify paths and (if appropriate) other variables for our system.

```

emacs config.py

```

## Deployment

Run absinth without modifiers to use the dataset path and with '-t' for the trial path.

```

python3 absinth.py

```

```

python3 absinth.py -t

```

## Built With

* [NetworkX](https://networkx.github.io/) - Graph implementation

* [NLTK](http://www.nltk.org/ - Stopwords

* [Spacy](https://spacy.io/) - Tokenisation and syntactic parsing

* [NumPy](http://www.numpy.org/) - Maths

## Authors

* **Maja Hoffmann** - [hoffmann](https://gitlab.cl.uni-heidelberg.de/hoffmann/)

* **Victor Zimmermann** - [zimmermann](http://www.cl.uni-heidelberg.de/~zimmermann/)

## License

This project is licensed under the MIT License - see the [LICENSE.md](LICENSE.md) file for details

## Acknowledgments

* In Loving Memory of Bente Nittka.