Hi,

as for corpora we could be using to train freely available models for
opennlp on: I have tested OANC (the "open" section of the american
national corpus, http://www.americannationalcorpus.org/OANC).

Although the OANC is automatically tagged, I obtain quite OK results
(sentence splitting, tokenization, POS Tagging, NP Chunking).

So, maybe we can provide models trained on OANC for download?

Moreover: Nancy Ide just told me, there was a subset of the OANC (called
MASK) which was manually validated and is also freely available. This
might be even better.

What do you think?

Best,
Katrin



On 02/20/2012 11:01 PM, Jason Baldridge wrote:
Might be some things we should look at wrt to our goals of creating
annotated resources. -j

---------- Forwarded message ----------
From: ELRA ELDA Information<[email protected]>
Date: Wed, Feb 15, 2012 at 7:36 AM
Subject: LREC 2012 Workshop on Language Resource Merging - Extended
Deadline to Feb. 22, 2012

To:


Call for Papers
LREC 2012 Workshop on: Language Resource Merging
22 May 2012 – Afternoon Session

EXTENDED Submission deadline: 22 FEBRUARY

CONTEXT
The availability of adequate language resources has been a well-known
bottleneck for most high-level language technology applications, e.g.
Machine Translation, parsing, and Information Extraction, for at least 15
years, and the impact of the bottleneck is becoming all the more apparent
with the availability of higher computational power and massive storage,
since modern language technologies are capable of using far more resources
than the community produces. The present landscape is characterized by the
existence of numerous scattered resources, many of which have differing
levels of coverage, types of information and granularity. Taken singularly,
existing resources do not have sufficient coverage, quality or richness for
robust large-scale applications, and yet they contain valuable information
(Monachini et al. 2004 and 2006; Soria et al. 2006; Molinero, Sagot and
Nicolas 2009; Necsulescu et al. 2011). Differing technology or application
requirements, ignorance of the existence of certain resources, and
difficulties in accessing and using them, has led to the proliferation of
multiple, unconnected resources that, if merged, could constitute a much
richer repository of information augmenting either coverage or granularity,
or both, and consequently multiplying the number of potential language
technology applications. Merging, combining and/or compiling larger
resources from existing ones thus appears to be a promising direction to
take.
The re-use and merging of existing resources is not altogether unknown. For
example, WordNet (Fellbaum, 1998) has been successfully reused in a variety
of applications. But this is the exception rather than the rule; in fact,
merging, and enhancing existing resources is uncommon, probably because it
is by no means a trivial task given the profound differences in formats,
formalisms, metadata, and linguistic assumptions.
The language resource landscape is on the brink of a large change, however.
With the proliferation of accessible metadata catalogues, and resource
repositories (such as the new META-SHARE (http://www.meta-net.eu/meta-**
share<http://www.meta-net.eu/meta-share>) infrastructure), a potentially
large number of existing resources will be more easily located, accessed
and downloaded. Also, with the advent of distributed platforms for the
automatic production of language resources, such as PANACEA (
http://www.panacea-lr.eu/), new language resources and linguistic
information capable of being integrated into those resources will be
produced more easily and at a lower cost. Thus, it is likely that
researchers and application developers will seek out resources already
available before developing new, costly ones, and will require methods for
merging/combining various resources and adapting them to their specific
needs.
Up to the present day, most resource merging has been done manually, with
only a small number of attempts reported in the literature towards
(semi-)automatic merging of resources (Crouch&  King 2005; Pustejovsky et
al. 2005; Molinero, Sagot and Nicolas 2009; Necsulescu et al. 2011). In
order to take a further step towards the scenario depicted above, in which
resource merging and enhancing is a reliable and accessible first step for
researchers and application developers, experience and best practices must
be shared and discussed, as this will help the whole community avoid any
waste of time and resources.

AIMS OF THE WORKSHOP
This half-day workshop is meant to be part of a series of meetings
constituting an ongoing forum for sharing and evaluating the results of
different methods and systems for the automatic production of language
resources (the first one was the LREC 2010 Workshop on Methods for the
Automatic Production of Language Resources and their Evaluation Methods).
The main focus of this workshop is on (semi-)automatic means of merging
language resources, such as lexicons, corpora and grammars. Merging makes
it possible to re-use, adapt, and enhance existing resources, alongside
new, automatically created ones, with the goal of reducing the manual
intervention required in language resource production, and thus ultimately
production costs.

WORKSHOP TOPICS
The topics of the workshop are related to best practices, methods,
techniques and experimental results regarding the merging of various types
of language resources, such as lexicons and corpora, especially in support
of language technology applications. In particular, new methods for
automatic merging with a view towards reducing human intervention will be
most welcome.
Topics for submission include, but are not limited to:
Experiments on (semi-)automatic merging of automatically produced resources
Experiments on the merging of two or more existing resources containing the
same or different levels of linguistic information
Studies or experiments on merging resources at different levels of
granularity (corpora, lexicons, grammars)
Studies or experiments on unifying, mapping or converting encoding formats
Comparison between different resources and mapping algorithms to provide
desired merging
Use of linguistic information from different sources in high-level language
applications
Use of new, merged language resources in language technology applications

WORKSHOP WEBSITE:
http://panacea-lr.eu/en/news/**project/2011/12/19/lrec-2012-**
merging-lr-workshop/<http://panacea-lr.eu/en/news/project/2011/12/19/lrec-2012-merging-lr-workshop/>

SUBMISSIONS
Interested participants must submit a preliminary paper of about 4-6 pages
including references (between 2000-2500 words). For the submission please
use the online form on START LREC Conference Manager at:
https://www.softconf.com/**lrec2012/MergingLR2012/<https://www.softconf.com/lrec2012/MergingLR2012/>
When submitting a paper from the START page, authors will be asked to
provide essential information about resources (in a broad sense, i.e. also
technologies, standards, evaluation kits, etc.) that have been used for the
work described in the paper or are a new result of your research.
For further information on this new initiative, please refer to
http://www.lrec-conf.org/**lrec2012/?LRE-Map-2012<http://www.lrec-conf.org/lrec2012/?LRE-Map-2012>
Papers will be peer-reviewed by the workshop Program Committee.

IMPORTANT DATES
Deadline for paper submission: 22 February 2012 (23:59 CET +1) **EXTENDED**
Notification of acceptance: 15 March 2012
Submission of camera-ready version of papers: 31 March 2012
Workshop date: 22 May 2012 – Afternoon Session

ORGANIZING COMMITTEE
Núria Bel, UPF, Barcelona, Spain
Maria Gavrilidou, ILSP-“Athena”, Athens, Greece,
Monica Monachini, CNR-ILC, Pisa, Italy
Valeria Quochi, CNR-ILC, Pisa, Italy
Laura Rimell, University of Cambridge, UK

Contacts
lrec12_workshop_merging@ilc.**cnr.it<[email protected]>

PROGRAMME COMMITTEE:
Victoria Arranz, ELDA, Paris, France
Paul Buitelaaar, National University of Ireland, Galway, Ireland
Nicoletta Calzolari, CNR-ILC, Pisa, Italy
Olivier Hamon, ELDA, Paris, France
Aleš Horák, Masaryk University, Brno, Czech Republic
Nancy Ide, Vassar College, Mass. USA
Bernardo Magnini, FBK, Trento, Italy
Paola Monachesi, Utrecht University, Utrecht, The Netherlands
Jan Odijk, , Utrecht University, Utrecht, The Netherlands
Muntsa Padró, IULA, Barcellona, Spain
Karel Pala, Masaryk University, Brno, Czech Republic
Thierry Poibeau University of Cambridge, UK and CNRS, Paris, France
Benoît Sagot, INRIA, Paris, France
Kiril Simov, Bulgarian Academy of Sciences, Sofia, Bulgaria
Claudia Soria, CNR-ILC, Pisa, Italy
Maurizio Tesconi, CNR-IIT, Pisa






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