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<p style="text-align: center;" align="center"><b>- <a href="#prize">Mark
Liberman, LDC
Director, wins the 2010 Antonio Zampolli Prize</a></b><b> -</b><o:p></o:p><br>
<b><br>
</b><i>New publications:</i><o:p></o:p></p>
<p style="text-align: center;" align="center">LDC2010T07<b><br>
</b><b>- </b><b><a href="#ctb">Chinese
Treebank 7.0</a> -</b><o:p></o:p></p>
<p style="text-align: center;" align="center">LDC2010T11<b><br>
</b><b>- </b> <a href="#open"><b>NIST
2003
Open Machine
Translation (OpenMT) Evaluation</b></a><b> -</b><o:p></o:p></p>
<p style="text-align: center;" align="center">LDC2010V01<b><br>
</b><b>- <a href="#trecvid">TRECVID
2004 Keyframes & Transcripts</a></b><b> -</b></p>
<p style="text-align: center;" align="center"><o:p></o:p></p>
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<hr align="center" size="2" width="100%"></div>
<p class="MsoNormal" style="text-align: center;" align="center"><a
name="prize"></a></p>
<p class="MsoNormal" style="text-align: center;" align="center"><b>Mark
Liberman, LDC Director, wins the 2010 Antonio
Zampolli Prize</b><o:p></o:p></p>
<p class="MsoNormal">LDC is proud to announce that our founder and
Director, Mark
Liberman, was awarded the 2010 <a
href="http://www.elra.info/Antonio-Zampolli-Prize.html">Antonio
Zampolli prize</a>
at <a href="http://www.lrec-conf.org/lrec2010/">LREC2010</a>, hosted
by <a href="http://www.elra.info/">ELRA</a>,
the
European Language Resource Association. This prestigious honor is given
by ELRA’s board members to
recognize “outstanding contributions to the advancement of language
resources
and language technology evaluation within human language
technologies”. <o:p></o:p></p>
<p class="MsoNormal"><o:p></o:p>Mark’s prize talk, delivered on <st1:date
month="5" day="21" year="2010">May 21, 2010</st1:date> and entitled <a
href="http://languagelog.ldc.upenn.edu/myl/AntonioZampolliPrizeLecture.pdf">The
Future of Computational Linguistics: or, What Would Antonio Zampolli Do?</a>,
discussed
Antonio Zampolli’s far-reaching contributions to the language
technology
community and how his vision resonates in Mark’s research. Please join
us in
congratulating Mark on receiving this award.<br>
</p>
<p class="MsoNormal">[<a href="#top">
top </a>]<br>
<o:p></o:p></p>
<p class="MsoNormal" style="margin-bottom: 12pt;">
</p>
<p class="MsoNormal" style="margin-bottom: 12pt;"><br>
<o:p></o:p></p>
<p style="text-align: center;" align="center"><b>New Publications</b><o:p></o:p></p>
<p><a name="ctb"></a>(1) <a
href="http://www.ldc.upenn.edu/Catalog/CatalogEntry.jsp?catalogId=LDC2010T07">C</a><a
href="http://www.ldc.upenn.edu/Catalog/CatalogEntry.jsp?catalogId=LDC2010T07">hinese
Treebank 7.0</a> consists of 840,000 words of annotated and parsed text
from
Chinese newswire, magazine news, and various broadcast news and
broadcast
conversation programs. The Chinese Treebank project began at the <st1:place><st1:placetype>University</st1:placetype>
of <st1:placename>Pennsylvania</st1:placename></st1:place> in 1998,
continued
at the <st1:place><st1:placetype>University</st1:placetype> of <st1:placename>Colorado</st1:placename></st1:place>,
and is in the process of moving to <a
href="http://www.cs.brandeis.edu/%7Ellc/page2/page2.html">Brandeis
University</a>.
The project provides a large, part-of-speech tagged and fully bracketed
Chinese
language corpus. The first deliveries provided syntactically annotated
words
from newswire texts. The annotation of broadcast news and broadcast
conversation data began and continues under the DARPA GALE (Global
Autonomous
Language Exploitation) program; Chinese Treebank 7.0 represents the
results of
that effort.<o:p></o:p></p>
<p>Chinese Treebank 7.0 includes text from the following genres and
sources.<o:p></o:p></p>
<table class="MsoNormalTable" style="width: 80%;" border="1"
cellpadding="0" width="80%">
<tbody>
<tr style="">
<td style="padding: 0.75pt; width: 39%;" width="39%">
<p class="MsoNormal"><strong>Genre</strong><o:p></o:p></p>
</td>
<td style="padding: 0.75pt; width: 61%;" width="61%">
<p class="MsoNormal"><strong># words</strong><o:p></o:p></p>
</td>
</tr>
<tr style="">
<td style="padding: 0.75pt;">
<p class="MsoNormal">Newswire (Xinhua)<o:p></o:p></p>
</td>
<td style="padding: 0.75pt;">250,000<br>
</td>
</tr>
<tr style="">
<td style="padding: 0.75pt;">
<p class="MsoNormal">News Magazine (Sinorama)<o:p></o:p></p>
</td>
<td style="padding: 0.75pt;">
<p class="MsoNormal">150,000<o:p></o:p></p>
</td>
</tr>
<tr style="">
<td style="padding: 0.75pt;">
<p class="MsoNormal">Broadcast News (CBS, CNR, CTS, CCTV, VOM)<o:p></o:p></p>
</td>
<td style="padding: 0.75pt;">
<p class="MsoNormal">270,000<o:p></o:p></p>
</td>
</tr>
<tr style="">
<td style="padding: 0.75pt;">
<p class="MsoNormal">Broadcast Conversation (CCTV, CNN, MSNBC, <st1:city><st1:place>Phoenix</st1:place></st1:city>)<o:p></o:p></p>
</td>
<td style="padding: 0.75pt;">
<p class="MsoNormal">170,000<o:p></o:p></p>
</td>
</tr>
<tr style="">
<td style="padding: 0.75pt;">
<p class="MsoNormal">Total<o:p></o:p></p>
</td>
<td style="padding: 0.75pt;">
<p class="MsoNormal">840,000<o:p></o:p></p>
</td>
</tr>
</tbody>
</table>
<p>The annotation of syntactic structure trees for the Chinese newswire
data
was taken from Chinese Treebank 5.0 and updated with some corrections.
Known
problems, like multiple tree nodes at the top level, were fixed.
Inconsistent
annotations for object control verbs were also corrected. The residual
Traditional Chinese characters in the Sinorama portion of the data, the
result
of incomplete automatic conversion, have been manually normalized to
Simplified
Chinese characters. <o:p></o:p></p>
<p>This release contains the frame files for each annotated verb or
noun, which
specify the argument structure (semantic roles) for each predicate. The
frame
files are effectively lexical guidelines for the propbank annotation.
The
semantic roles annotated in this data can only be interpreted with
respect to
these frame files. The annotation of the verbs in the Xinhua news
portion
of the data is taken from <a
href="http://www.ldc.upenn.edu/Catalog/CatalogEntry.jsp?catalogId=LDC2005T23">Chinese
Proposition Bank 1.0 (LDC2005T23)</a>. The annotation of the
predicate-argument
structure of the included nouns, which are primarily nominalizations,
has not
been previously released. The Sinorama portion of the data, both for
verbs and
nouns, has not been previously released.<o:p></o:p></p>
<br>
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<o:p></o:p></p>
<p class="MsoNormal" style="text-align: center;" align="center">*<o:p></o:p></p>
<p><br>
<a name="open"></a>(2) <a
href="http://www.ldc.upenn.edu/Catalog/CatalogEntry.jsp?catalogId=LDC2010T11">NIST
2003 Open Machine Translation (OpenMT) Evaluation</a> is a package
containing
source data, reference translations, and scoring software used in the
NIST 2003
OpenMT evaluation. It is designed to help evaluate the effectiveness of
machine
translation systems. The package was compiled and scoring software was
developed by researchers at NIST, making use of newswire source data
and
reference translations collected and developed by LDC. <o:p></o:p></p>
<p class="MsoNormal">The objective of the NIST OpenMT evaluation series
is to
support research in, and help advance the state of the art of, machine
translation (MT) technologies -- technologies that translate text
between human
languages. Input may include all forms of text. The goal is for the
output to
be an adequate and fluent translation of the original. Additional
information
about these evaluations may be found at the <a
href="http://www.itl.nist.gov/iad/mig/tests/mt/">NIST Open Machine
Translation
(OpenMT) Evaluation web site</a>. <o:p></o:p></p>
<p>This evaluation kit includes a single perl script that may be used
to
produce a translation quality score for one (or more) MT systems. The
script
works by comparing the system output translation with a set of (expert)
reference translations of the same source text. Comparison is based on
finding
sequences of words in the reference translations that match word
sequences in
the system output translation.<o:p></o:p></p>
<p>The Chinese-language and Arabic-language source text included in
this corpus
is a reorganization of data that was initially released to the public
respectively as <a
href="http://www.ldc.upenn.edu/Catalog/CatalogEntry.jsp?catalogId=LDC2006T04">Multiple-Translation
Chinese (MTC) Part 4 (LDC2006T04)</a> and <a
href="http://www.ldc.upenn.edu/Catalog/CatalogEntry.jsp?catalogId=LDC2005T05">Multiple-Translation
Arabic (MTA) Part 2 (LDC2005T05)</a>. The reference translations are a
reorganized subset of data from these same Multiple-Translation
corpora. All
source data for this corpus is newswire text collected in January and
February
of 2003 from Agence France-Presse, and Xinhua News Agency. For details
on the
methodology of the source data collection and production of reference
translations, see the documentation for the above-mentioned corpora.<o:p></o:p></p>
<p>For each language, the test set consists of two files, a source and
a
reference file. Each reference file contains four independent
translations of
the data set. The evaluation year, source language, test set, version
of the
data, and source vs. reference file are reflected in the file name.<o:p></o:p></p>
<br>
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<o:p></o:p></p>
<p class="MsoNormal" style="text-align: center;" align="center">*<o:p></o:p></p>
<p><a name="trecvid"></a>(3) <a
href="http://www.ldc.upenn.edu/Catalog/CatalogEntry.jsp?catalogId=LDC2010V01">TRECVID
2004 Keyframes and Transcripts</a> was developed as a collaborative
effort
between researchers at LDC, <a href="http://www.nist.gov/">NIST</a>, <a
href="http://www.limsi.fr/">LIMSI-CNRS</a>, and <a
href="http://www.dcu.ie/">Dublin
City University</a>. TREC Video Retrieval Evaluation (TRECVID) is
sponsored by the National Institute of Standards and Technology (NIST)
to
promote progress in content-based retrieval from digital video via
open,
metrics-based evaluation. The keyframes in this release were extracted
for use
in the NIST TRECVID 2004 Evaluation. TRECVID is a laboratory-style
evaluation that attempts to model real world situations or significant
component
tasks involved in such situations. In 2004 there were four main tasks
with
associated tests: <o:p></o:p></p>
<ul type="disc">
<li class="MsoNormal" style="">shot boundary determination <o:p></o:p></li>
<li class="MsoNormal" style="">story segmentation <o:p></o:p></li>
<li class="MsoNormal" style="">high-level feature extraction <o:p></o:p></li>
<li class="MsoNormal" style="">search (interactive and manual) <o:p></o:p></li>
</ul>
<p>For a detailed description of the TRECVID Evaluation Tasks, please
refer to
the <a href="http://www-nlpir.nist.gov/projects/tv2004/">NIST TRECVID
2004
Evaluation Description.</a> <o:p></o:p></p>
<p>The source data includes approximately 70 hours of English language
broadcast programming collected by LDC in 1998 from ABC ("World News
Tonight") and CNN ("CNN Headline News"). <o:p></o:p></p>
Shots are fundamental units of video, useful for
higher-level processing. To create the master list of shots, the video
was
segmented. The results of this pass are called subshots. Because the
master
shot reference is designed for use in manual assessment, a second pass
over the
segmentation was made to create the master shots of at least 2 seconds
in
length. These master shots are the ones used in submitting results for
the
feature and search tasks in the evaluation. In the second pass,
starting at the
beginning of each file, the subshots were aggregated, if necessary,
until the
current shot was at least 2 seconds in duration, at which point the
aggregation
began anew with the next subshot. <br>
<br>
The keyframes were selected by going to the middle frame of the shot
boundary,
then parsing left and right of that frame to locate the nearest
I-Frame. This
then became the keyframe and was extracted. Keyframes have been
provided at
both the subshot (NRKF) and master shot (RKF) levels. <br>
<br>
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<div align="center">
<pre class="moz-signature" cols="72"><big><font
face="Courier New, Courier, monospace"><small><small><big>Ilya Ahtaridis</big></small></small></font>
<font face="Courier New, Courier, monospace"><small><small><big>Membership Coordinator</big></small></small></font></big>
<font face="Courier New, Courier, monospace"><small>--------------------------------------------------------------------</small></font>
<font face="Courier New, Courier, monospace">Linguistic Data Consortium Phone: (215) 573-1275
University of Pennsylvania Fax: (215) 573-2175
3600 Market St., Suite 810 <a
class="moz-txt-link-abbreviated" href="mailto:ldc@ldc.upenn.edu">ldc@ldc.upenn.edu</a>
Philadelphia, PA 19104 USA <a
class="moz-txt-link-freetext" href="http://www.ldc.upenn.edu">http://www.ldc.upenn.edu</a></font></pre>
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<pre class="moz-signature" cols="72">
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