Welcome to the Subtask 1 of the MADAR Shared Task on Arabic Fine-Grained Dialect Identification, organized at The Fourth Arabic Natural Language Processing Workshop (WANLP 2019). In subtask 1, participants are provided with a large-scale collection of parallel sentences in the travel domain covering the dialects of 25 cities from the Arab World plus standard Arabic (MSA). The task is to build systems that predict a dialect class among one of the 26 labels (25+ MSA) for given sentences.
Number of runs submitted: <1,2,3>
Participants: <person1> <email> <affiliation> <country>
<person2> <email> <affiliation> <country>
Resources used: <dictionary X>, <corpus Y>, ...
Tools used: <POS tagger X>, <IR system Y>, <word alignment system Z>,
<machine learning library T>, ...
Techniques used: Any special techniques or insights
Systems will be evaluated using Macro Averaged F1-score.
Submission format information is available from the 'Participate' tab above.
The performance of submitted systems will be evaluated on
MADAR-Corpus26-test.tsv which will be made available during the
evaluation phase. MADAR-Corpus6-train.tsv and
MADAR-Corpus6-dev.tsv are provided to aid building the models.
Participants are welcome to use both of these files for training
The training data from MADAR-Shared-Task-Subtask-2 is allowed.
External manually labelled data sets are *NOT* allowed.
However, the use of publicly available unlabelled data is allowed.
IMPORTANT: Participants are NOT allowed to use
MADAR-Corpus26-dev.tsv for training purposes. Participants must
report the performance of their best system on
MADAR-Corpus26-dev.tsv in their Shared Task system description
Copyright 2018 Carnegie Mellon University and New York University Abu
Dhabi. All Rights Reserved.
A license to use and copy this dataset and its documentation solely
for your internal research and evaluation purposes, without fee and
without a signed licensing agreement, is hereby granted upon your
download of the dataset, through which you agree to the following: 1)
the above copyright notice, this paragraph and the following three
paragraphs will prominently appear in all internal copies and
modifications; 2) no rights to sublicense or further distribute this
software are granted; 3) no rights to modify this dataset are granted;
and 4) no rights to assign this license are granted. Please Contact
the Carnegie Mellon University “CMU” Center for Technology Transfer
and Enterprise Creation, 4615 Forbes Avenue, Suite 302, Pittsburgh, PA
15213 - phone 412.268.7393, for commercial licensing opportunities, or
for further distribution, modification or license rights.
Created by Houda, Bouamor, Nizar Habash, Mohammad Salameh, Wajdi
Zaghouani, Owen Rambow, Dana Abdulrahim, Ossama Obeid, Salam Khalifa,
Fadhl Eryani, Alexander Erdmann and Kemal Oflazer.
IN NO EVENT SHALL CMU OR NYU, OR THEIR EMPLOYEES, OFFICERS, AGENTS OR
TRUSTEES ("COLLECTIVELY "CMU/NYU PARTIES") BE LIABLE TO ANY PARTY FOR
DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR CONSEQUENTIAL DAMAGES OF ANY
KIND, INCLUDING LOST PROFITS, ARISING OUT OF ANY CLAIM RESULTING FROM
YOUR USE OF THIS DATASET AND ITS DOCUMENTATION, EVEN IF ANY OF CMU/NYU
PARTIES HAS BEEN ADVISED OF THE POSSIBILITY OF SUCH CLAIM OR DAMAGE.
CMU/NYU SPECIFICALLY DISCLAIMS ANY WARRANTIES OF ANY KIND REGARDING
THE DATASET, INCLUDING, BUT NOT LIMITED TO, NON-INFRINGEMENT, THE
IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
PURPOSE, OR THE ACCURACY OR USEFULNESS, OR COMPLETENESS OF THE
SOFTWARE. THE SOFTWARE AND ACCOMPANYING DOCUMENTATION, IF ANY,
PROVIDED HEREUNDER IS PROVIDED COMPLETELY "AS IS". REGENTS HAS NO
OBLIGATION TO PROVIDE FURTHER DOCUMENTATION, MAINTENANCE, SUPPORT,
UPDATES, ENHANCEMENTS, OR MODIFICATIONS.
If you use this resource, cite:
Bouamor, Houda, Nizar Habash, Mohammad Salameh, Wajdi Zaghouani, Owen
Rambow, Dana Abdulrahim, Ossama Obeid, Salam Khalifa, Fadhl Eryani,
Alexander Erdmann and Kemal Oflazer. The MADAR Arabic Dialect Corpus
and Lexicon. In Proceedings of the International Conference on
Language Resources and Evaluation (LREC 2018), Miyazaki, Japan, 2018.
Start: April 9, 2019, midnight
Start: May 5, 2019, midnight
May 18, 2019, noon
You must be logged in to participate in competitions.Sign In