[Mt-list] MT Summit Workshop on Qualities in Literary Machine Translation

[Maja Popovic]

Interested in literary machine translation?
Submit a 300-word abstract to the MT Summit Workshop
"The Qualities of Literary Machine Translation":
https://www.academia.edu/38505151/Machine_Translation_Summit_2019_Workshop_Call_for_Papers_The_Qualities_of_Literary_Machine_Translation?source=swp_share

Deadline:
15 May 2019

Workshop date and location:
19 August 2019, Dublin, Ireland
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[Mt-list] [NSURL Task 9 and 10]: Low-level NLP Tools for Magahi and Bhojpuri Shared Task under the NSURL-2019.

[Atul Kr. Ojha]

Apologies for cross-posting. You are requested to please circulate it for
wider publicity

.
...

*Shared Task  on Low-level NLP Tools for Magahi and Bhojpuri*


*Workshop Date*: *11-12 September 2019*
Venue: *Department of Information Engineering and Computer Science -DISI*,
University of Trento, Italy (Organized under Workshop on NLP Solutions for
Under Resourced Languages (11-12 September 2019)

*Website:*
*Main website* - http://nsurl.org/ 
*Shared Task for Magahi:*
http://nsurl.org/tasks/task-9-low-level-nlp-tools-for-magahi-language/
*Shared Task for Bhojpuri:*
http://nsurl.org/tasks/task-10-low-level-nlp-tools-for-bhojpuri-language/
*Registration Link:*
https://docs.google.com/forms/d/1UHzelcIpitpD4njv3hTIkwRiOAye5Fzkz_aCeJiYmBU/edit?ts=5c7b6f7c
*Submit papers on -* https://easychair.org/conferences/?conf=nsurl2019


-

*Task Description *
=
The task is to develop low-level NLP tools for Magahi and Bhojpuri. Both
Magahi and Bhojpuri are Eastern Indo-Aryan languages spoken largely in the
Eastern states of Bihar, Jharkhand and Uttar Pradesh in India. These
languages are part of what is considered a dialect continuum running the
Eastern part of India to its Weatern part and consisting of approximately
50 languages / varieties. Hindi, the official language of India, is part of
the same continuum and as such these are closely related to each other.
However, despite this similarity, these languages have large divergences in
terms of lexicon as well as morphological make-up. As such most of the
tools developed for Hindi do not perform very well with the other
languages. For this task, we are providing small annotated datasets for
Magahi and Bhojpuri in order to develop part-of-speech tagger and
morphological analyser for these languages. The dataset is annotated with
the part of speech categories and morphological features from Universal
Dependencies tagset.

*Sub tasks *
===
The task 9 and 10 has 2 sub-tasks -
A. POS tagger for each language
b. Number, Gender, Person, Tense, Aspect, Honorificity and Case relation
analyser for each language

*Data *
==
We will provide 5,000 annotated sentences (in CONLL-U format) for each of
the 2 languages. In addition to this, participants are also encouraged to
use the Hindi dataset available with Universal Dependencies project.
Additionally they are free to use any other dataset as long as the dataset
is freely available for research.

*Evaluation Procedure*
===
The standard evaluation metrics for evaluating and ranking the teams will
be macro-averaged F1 scores.

*Baseline *
=
The simple probabilistic baseline (the most frequent tags get assigned to
each token) will be provided by the organisers.

*Important Dates *

Training dataset will be made available by *15th April, 2019*. Other
deadlines are as per the workshop schedule.


*Results *
=
Results will be made available as per the workshop schedule

*Paper submission*
==
Paper submission instructions will be same as for the workshop

*Task Organizers *

If you have any queries regarding this task, please refer to the task
organizers:

*Ritesh Kumar*, Dr. B.R. University Agra, India
*Atul Kumar Ojha*, Panlingua Language Processing LLP and JNU, New Delhi,
India

*Regarding Query:*

If you have any queries regarding this task, please send an email at
nlp-...@googlegroups.com




Thanks and regards,
Atul Kr. Ojha
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