CoNLL 2017 Shared Task in parsing Universal Dependencies

We are happy to announce the CoNLL 2017 Shared Task:

Multilingual Parsing from Raw Text to Universal Dependencies

Website: http://universaldependencies.org/conll17/
Email contact: ud.conll.shared.task.2017@gmail.com

Ten years ago, two CoNLL shared tasks were a major milestone for
parsing research in general and dependency parsing in particular.
For the first time dependency treebanks in more than ten languages
were available for learning parsers; many of them were used in
follow-up work, evaluating parsers on multiple languages became a
standard; and multiple state-of-the art, open-source parsers became
available, facilitating production of dependency structures to be
used in downstream applications. While the 2006 & 2007 tasks were
extremely important in setting the scene for the following years,
there were also limitations that complicated application of their
results: 1. gold-standard tokenization and tags in the test data
moved the tasks away from real-world scenarios, and 2. incompatible
annotation schemes made cross-linguistic comparison impossible.
CoNLL 2017 will pick up the threads of the pioneering tasks and
address the two issues just mentioned.

The focus of the 2017 task is learning syntactic dependency parsers
that can work in a real-world setting, starting from raw text, and
that can work over many typologically different languages, even
surprise languages for which there is little or no training data,
by exploiting a common syntactic annotation standard. This task has
been made possible by the Universal Dependencies initiative (UD,
http://universaldependencies.org/ ), which has developed treebanks
for 40+ languages with cross-linguistically consistent annotation
and recoverability of the original raw texts. For the Shared Task,
the annotation scheme called ?Universal Dependencies version 2?, or
?UD v2? for short will be used.

Participants will get UD treebanks in many languages, with raw
text, gold-standard sentence and word segmentation, POS tags,
dependency relations, and in many cases also lemmas + morphological
features. The test data will contain none of the gold-standard
annotations, but baseline predicted segmentation and POS tags will
be available. Labeled attachment score (LAS) will be computed for
every test set, and the macro-average of the scores over all test
sets will provide the main system ranking.

The test sets will include a few surprise languages. We will not
provide training data for these languages, only a small sample
shortly before the test phase. To succeed in parsing these
languages, systems will have to employ low-resource language
techniques, utilizing data from other languages.

There will be no separate open and closed tracks. Instead, we will
include every system in a single track, which will be formally
closed, but where the list of permitted resources is rather broad
and includes large raw corpora and parallel corpora.

Participating systems will have to find labeled syntactic
dependencies between words, i.e. a syntactic head for each word,
and a label classifying the type of the dependency relation.
Participants will parse raw text where no gold-standard
pre-processing (tokenization, lemmas, morphology) is available.
However, there are at least two open-source pipelines (UDPipe,
https://ufal.mff.cuni.cz/udpipe/ , and SyntaxNet, https://www .
tensorflow.org/versions/r0.9/tutorials/syntaxnet/index.html) that
the participants can run instead of training their own models for
any steps preceding the dependency analysis. We will even provide
variants of the test data that have been preprocessed by UDPipe. We
believe that this makes the task reasonably accessible.

The task is open to everyone. The organizers rely, as is usual in
large shared tasks, on the honesty of all participants who might
have some prior knowledge of part of the data that will eventually
be used for evaluation, not to unfairly use such knowledge. The
only exception is the chair of the organizing team, who cannot
submit a system, and who will serve as an authority to resolve any
disputes concerning ethical issues or completeness of system
descriptions.

Timeline:

December 11 ? announcement of the shared task and set up of the shared task website. Registration for the Shared Task open.
January 10 ? deadline for suggesting additional data by participants (registration necessary)
February 20 ? trial data for a few languages will be available
February 28 ? task Registration deadline. Participants have to register to setup their evaluation space and other data, and to get access to task data later.
March 1 ? training and development data will be released
May 1 ? surprise languages will be announced and small sample data released
May 8 ? 12 ? test phase
May 15 ? results will be announced
May 26 ? submission of system description papers
June 2 ? reviews due
June 9 ? final papers due
August 3 ? 4 ? CoNLL, Vancouver, Canada

See http://universaldependencies.org/conll17/ for more information.

Об авторе Лидия Пивоварова

СПбГУ - старший преподаватель, University of Helsinki - PhD student http://philarts.spbu.ru/structure/sub-faculties/itah_phil/teachers/pivovarova
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