Coreference annotation tool (SACR)

SACR (from the French "Script d'Annotation des Chaînes de Référence") is a tool optimized for coreference chain annotation.

It has been published in the following paper:

Oberle B. (2018). SACR: A Drag-and-Drop Based Tool for Coreference Annotation. Proceedings of the 11th Edition of the Language Resources and Evaluation Conference (LREC 2018). Miyazaki, Japan (poster)

use it now! download code view github repo see the user guide watch tutorials (YouTube)

On this page:

Workflow

SACR is a single webpage. All operations are done in the browser. You can download the code and open the index.html file, or use it online (see links above).

The workflow is as follows:

(1) Mark the referring expressions:

(2) Build the coreference chains:

(3) Add feature annotations:

(4) Play and search:

Getting help

Documentation can be found in the user_guide.pdf file. It is a work in progress, with some English sections to be done. It has not yet been proof-read.

I have made some video tutorials in French, available on YouTube (see also the playlist) (these links open in new window or tab):

Convert all the annotation into a relational database

Use the coreference database project scripts to convert your work into a relational database, in the form of a series of CSV (Comma Separated Values) files, that you can use in a spreadsheet program like Microsoft Office or LibreOffice Calc, or in a specialized statistic program like R or Python's Pandas.

This works for a single text or a whole corpus (several texts separately annotated with SACR).

The table (CSV files) are:

Note that there is simpler beta version available online here.

Conversion scripts to other formats

From other coreference formats

See the corefconversion project to convert to and from Conll and other formats.

From and To Glozz and TXM

You can convert between formats online (offline while updating the new website):

You can also download the following Perl scripts to perform the conversion on your own computer:

To export and import to TXM: