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<div class="moz-cite-prefix">FYI,<br>
Sebastian<br>
<br>
On 15.07.2014 17:18, Feiyu Xu wrote:<br>
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<blockquote cite="mid:8406D1A3-5E19-4E56-AA7F-7E4A5EE0585A@dfki.de"
type="cite">
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<div style="font-family: Arial;">Apologies for cross-posting</div>
<div style="font-family: Arial;">Please forward this message to
colleagues in the areas of interest</div>
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=============================<br>
RESOURCE ANNOUNCEMENT<br>
RELEASE OF sar-graph 1.0<br>
<a class="moz-txt-link-freetext" href="http://">http://</a><a moz-do-not-send="true"
href="http://sargraph.dfki.de">sargraph.dfki.de</a><br>
=============================
<div><br>
The following resource will be released on META-SHARE and is
already available as a pre-release at <a moz-do-not-send="true"
href="http://sargraph.dfki.de">http://sargraph.dfki.de</a>.
<div><br>
A <b>sar-graph</b> is a graph containing linguistic knowledge
at syntactic and lexical semantic levels for a given language
and target relation. a sar-graph for a targeted relation
assembles many linguistic patterns that are used in texts to
mention this relation. The term semantically associated
relations graph was chosen since the patterns may either
express the target relation directly or by expressing a
semantically associated relation. The nodes in a sar-graph are
either semantic arguments of a target relation or content
words (to be more exact, their word senses) needed
to express/recognize an instance of the target relation. The
nodes are connected by two kinds of edges: syntactic
dependency structure relations and lexical semantic relations.
Thus they are labelled with dependency-structure tags provided
by a parser or lexical-semantic relation tags. A definition
can be found in (Uszkoreit and Xu, 2013). The individual
patterns are assembled in one graph per target relation for an
easier combination of mentions gathered across sentences, but
all patterns could also be employed individually. <br>
<br>
<b>From Strings to Things <br>
SAR-Graphs: A New Type of Resource for Connecting Knowledge
and Language</b><br>
Hans Uszkoreit and Feiyu Xu (2013) <br>
In Proceedings of 1st International Workshop on NLP and
DBpedia (NLP&DBPedia), volume 1064, Sydney,
NSW, Australia, CEUR Workshop Proceedings, 10/2013<br>
<br>
The current sar-graph version 1.0 contains syntactic
dependency relations between content words. In future
versions, we will integrate lexical semantic relations between
word senses.
<div><br>
</div>
<div>In the current version, the patterns have been
automatically learned by the web-scale version <b>Web-DARE</b> (Krause
et al., 2012) of the relation extraction system <b>DARE </b>(Xu
et al., 2007) from dependency structures obtained by parsing
sentential mentions of the target relation. DARE patterns
contain the content words that signal the
mentioned (semantically associated) relation and by the
syntactic dependencies that combine these words and link
them with the phrases representing the arguments of
the target relation. Thus, a sar-graph is composed of
syntactic dependency graphs. Their edges denote dependency
relations. Each edge is labeled with the tag the parser has
assigned to the dependency. Vertices come in two flavors:
One type of vertices denotes a regular node in a dependency
structure, thus it is labeled with a word. Vertices of the
second type represent the slots for the arguments of the
target relation, instead of a word, they are labeled by the
name of the argument, e.g. Person_1. Several dependency
parsers have been employed, but the current set of
sar-graphs is built from parsing results of the MALT parser.<br>
<br>
Applications of sar-graphs are information extraction,
question answering and summarisation. </div>
<div>The resource might also be useful for research on
paraphrases, textual entailment and syntactic variation
within a language.<br>
<br>
Release 1.0 has the following properties:<br>
<br>
Language: English <br>
Number of target relations: 25<br>
Arity of relations: n-ary relations (2≤n≤5)</div>
<div>Domains of relations: biographic information,
corporations, awards<br>
Format of patterns: DARE patterns in lemon format and
specific xml schema (DTD provided)<br>
Format of sar-graphs: specific xml schema (DTD provided)<br>
APIs: java api for reading and storing patterns and
sar-graphs,<br>
<span class="Apple-tab-span" style="white-space: pre;"> </span>java
api for various use cases: getting and searching for vertex,
edge information of a DARE pattern and a sar-graph,<br>
<span class="Apple-tab-span" style="white-space: pre;"> </span>java
api for pattern visualization<br>
<br>
<b>Download </b>is available at: <a moz-do-not-send="true"
href="http://sargraph.dfki.de/download.html">http://sargraph.dfki.de/download.html</a></div>
<div>More <b>statistics</b> are available at: <a
moz-do-not-send="true"
href="http://sargraph.dfki.de/statistics.html">http://sargraph.dfki.de/statistics.html</a><br>
More <b>references</b> can be found at: <a
moz-do-not-send="true"
href="http://sargraph.dfki.de/publications.html">http://sargraph.dfki.de/publications.html</a>
<div><b>Feedback</b> via email: <a moz-do-not-send="true"
href="mailto:sargraph@dfki.de">sargraph@dfki.de</a></div>
<div><br>
</div>
<div>sar-graphs were conceived and defined at DFKI LT-Lab
Berlin and then realized in </div>
<div>a collaboration between DFKI LT-Lab and the BabelNet
group at Sapienza University of Rome.</div>
<div><br>
The development of sar-graphs is partially supported by <br>
<div><span class="Apple-tab-span" style="white-space:
pre;"> </span>• the German Federal Ministry of
Education and Research (BMBF) through the
project Deependance (contract 01IW11003)<br>
</div>
<div><span class="Apple-tab-span" style="white-space:
pre;"> </span>• the project LUcKY, a Google Focused
Research Award in the area of Natural Language
Understanding. </div>
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<div>Enjoy!</div>
</div>
</div>
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<div>Feiyu Xu</div>
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<div><br
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----------------------------------</div>
<div>Dr. Feiyu Xu</div>
<div><br>
</div>
<div>Senior Researcher</div>
<div>Project Leader</div>
<div><br>
</div>
<div>DFKI Projektbüro Berlin</div>
<div>Alt Moabit 91c</div>
<div>D-10559 Berlin</div>
<div>Germany<br>
Phone +49-30-<span
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Sek +49-30-<span
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<div>E-mail: <a
moz-do-not-send="true"
href="mailto:feiyu@dfki.de">feiyu@dfki.de</a></div>
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<div>homepage: <a
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href="http://www.dfki.de/%7Efeiyu">http://www.dfki.de/~feiyu</a></div>
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<div>------------------------------------------------------------</div>
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<div>Deutsches Forschungszentrum
fuer Kuenstliche Intelligenz
GmbH</div>
<div>Firmensitz: Trippstadter
Strasse 122, D-67663
Kaiserslautern</div>
<div>Geschaeftsfuehrung:</div>
<div>Prof. Dr. Dr. h.c. mult.
Wolfgang Wahlster (Vorsitzender)</div>
<div>Dr. Walter Olthoff</div>
<div><br
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<div>Vorsitzender des
Aufsichtsrats:</div>
<div>Prof. Dr. h.c. Hans A. Aukes</div>
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</div>
<div>Amtsgericht Kaiserslautern,
HRB 2313</div>
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<br>
<div class="moz-signature">-- <br>
<small>Sebastian Hellmann<br>
AKSW/NLP2RDF research group<br>
Insitute for Applied Informatics (InfAI) and DBpedia Association<br>
Events: <br>
* <b>Sept. 1-5, 2014</b> Conference Week in Leipzig, including
<br>
** <b>Sept 2nd</b>, MLODE 2014 <br>
** <b>Sept 3rd</b>, 2nd DBpedia Community Meeting<br>
** <b>Sept 4th-5th</b>, <a href="http://semantics.cc/">SEMANTiCS
(formerly i-SEMANTICS) </a><br>
Venha para a Alemanha como PhD: <a
href="http://bis.informatik.uni-leipzig.de/csf">http://bis.informatik.uni-leipzig.de/csf</a><br>
Projects: <a href="http://dbpedia.org">http://dbpedia.org</a>,
<a href="http://nlp2rdf.org">http://nlp2rdf.org</a>, <a
href="http://linguistics.okfn.org">http://linguistics.okfn.org</a>,
<a href="http://www.w3.org/community/ld4lt">https://www.w3.org/community/ld4lt</a><br>
Homepage: <a href="http://aksw.org/SebastianHellmann">http://aksw.org/SebastianHellmann</a><br>
Research Group: <a href="http://aksw.org">http://aksw.org</a><br>
Thesis:<br>
<a href="http://tinyurl.com/sh-thesis-summary">http://tinyurl.com/sh-thesis-summary</a><br>
<a href="http://tinyurl.com/sh-thesis">http://tinyurl.com/sh-thesis</a><br>
</small></div>
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