<commit_before># cort

__cort__ is a <b>co</b>reference <b>r</b>esolution <b>t</b>oolkit. It
implements the coreference resolution error analysis framework described in 
our [EMNLP'14](#references) and [NAACL'15 demo](#references) papers, and also 
ships with well-performing deterministic and learning-based coreference 
resolution systems. 

If you have any questions or comments, drop me an e-mail at 
[<EMAIL>](mailto:<EMAIL>).

## Installation

__cort__ is available on PyPi. You can install it via

```
pip install cort
```

Dependencies are [nltk](http://www.nltk.org/), [numpy](http://www.numpy.org/), 
[matplotlib](http://matplotlib.org), 
[mmh3](https://pypi.python.org/pypi/mmh3) and
[future](https://pypi.python.org/pypi/future). __cort__ is written for use on 
Linux with either Python 2.7+ or Python 3.3+.

## Error Analysis

With __cort__, you can analyze recall and precision errors of your coreference 
resolution systems just with a few lines in python. Let us go through an 
example.

### Reading in Data

So far, __cort__ only supports data in [the format from the CoNLL shared tasks 
on coreference resolution](http://conll.cemantix.org/2012/data.html). Let us 
assume that you have some data in this format: all documents with reference 
annotations are in the file `reference.conll`. You have output of two 
coreference resolution systems, the output of the first system is in the file<commit_msg>Updated to status of NAACL'15 paper.<commit_after># cort

__cort__ is a <b>co</b>reference <b>r</b>esolution <b>t</b>oolkit. It
implements the coreference resolution error analysis framework described in 
our [EMNLP'14](#references) and [NAACL'15 demo](#references) papers, and also 
ships with well-performing deterministic and learning-based coreference 
resolution systems. 

If you have any questions or comments, drop me an e-mail at 
[<EMAIL>](mailto:<EMAIL>).

## Installation

Dependencies are [nltk](http://www.nltk.org/), [numpy](http://www.numpy.org/), 
[matplotlib](http://matplotlib.org), 
[mmh3](https://pypi.python.org/pypi/mmh3) and
[future](https://pypi.python.org/pypi/future). __cort__ is written for use on 
Linux with either Python 2.7+ or Python 3.3+.

## Error Analysis

With __cort__, you can analyze recall and precision errors of your coreference 
resolution systems just with a few lines in python. Let us go through an 
example.

### Reading in Data

So far, __cort__ only supports data in [the format from the CoNLL shared tasks 
on coreference resolution](http://conll.cemantix.org/2012/data.html). Let us 
assume that you have some data in this format: all documents with reference 
annotations are in the file `reference.conll`. You have output of two 
coreference resolution systems, the output of the first system is in the file
{'fraction_non_alphanumeric': 0.101725377426312, 'fraction_numerical': 0.010783608914450037, 'mean_word_length': 4.6680244399185336, 'pattern_counts': {'":': 0, '<': 19, '<?xml version=': 0, '>': 19, 'https://': 4, 'lorem ipsum': 0, 'www.': 4, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'dir': 'git-commits-cleaned', 'id': '2381122', 'n_tokens_mistral': 904, 'n_tokens_neox': 857, 'n_words': 335}