[Corpora-List] SemEval 2014 Task 8: Broad-Coverage Semantic Dependency Parsing

[Stephan Oepen]

[with apologies for cross-posting]

We would like to kindly invite participants to Task 8 at SemEval 2014:

  Broad-Coverage Semantic Dependency Parsing
    http://alt.qcri.org/semeval2014/task8/

This task seeks to stimulate the statistical parsing community to move
towards graph-structured target representations, to facilitate semantic
dependency parsing, i.e. an analysis of ‘Who did What to Whom’.  In the
task setup, there is similarity to both data-driven dependency parsing
and semantic role labeling.  Besides practitioners from these ‘classic’
tasks, we further hope to attract participants with a general interest
in natural language processing in terms of graph-shaped structures.

Please see the attachment for a sample of semantic dependency graphs as
used in this task.  Here, the goal is to incorporate all content words
in one semantic dependency graph, where bi-lexical dependencies encode
predicate–argument relations, and argument sharing is reflected through
re-entrancies in the graph, for example representing control relations.

As training data, we provide about 750,000 tokens of English newspaper
text annotated with gold-standard semantic dependency graphs of three
different types (as exemplified in the attachment: DM, PAS, and PCEDT).
All data is aligned at the sentence and token levels and distributed in
a uniform file format.  Test data will be drawn from the same genre.

The task offers a closed and an open track, and participants are free
to submit to either one or both.  In the closed track, systems can be
trained only on the data provided for the task, whereas the open track
makes it possible to use additional resources, e.g. a syntactic parser.

Following the common SemEval 2014 schedule, training data will become
available in mid-December, and evaluation will be towards the end of
March 2014.  Please see the task web pages for further details:

  http://alt.qcri.org/semeval2014/task8/

We ask all interested parties to self-subscribe to the mailing list for
this task: the subscription link is available from the above web page.

Please do not hesitate to contact the task organizers for questions or
clarifications, using the email address provided on the task web pages.

Dan Flickinger, Jan Hajič, Marco Kuhlmann, Yusuke Miyao,
Stephan Oepen, Yi Zhang, and Daniel Zeman
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