https://wikipediaquality.com/index.php?title=Exploiting_Syntactic_and_Semantic_Information_for_Relation_Extraction_from_Wikipedia&feed=atom&action=historyExploiting Syntactic and Semantic Information for Relation Extraction from Wikipedia - Revision history2024-03-29T12:35:31ZRevision history for this page on the wikiMediaWiki 1.30.0https://wikipediaquality.com/index.php?title=Exploiting_Syntactic_and_Semantic_Information_for_Relation_Extraction_from_Wikipedia&diff=26595&oldid=prevCress: + categories2021-01-12T17:55:43Z<p>+ categories</p>
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</table>Cresshttps://wikipediaquality.com/index.php?title=Exploiting_Syntactic_and_Semantic_Information_for_Relation_Extraction_from_Wikipedia&diff=26442&oldid=prevMadeleine: Adding embed2021-01-04T21:58:31Z<p>Adding embed</p>
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<td colspan="2" style="background-color: white; color:black; text-align: center;">Revision as of 21:58, 4 January 2021</td>
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<tr><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"><div>== Overview ==</div></td><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"><div>== Overview ==</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"><div>The exponential growth of [[Wikipedia]] recently attracts the attention of a large number of researchers and practitioners. One of the current challenge on Wikipedia is to make the encyclopedia processable for machines. In this paper, authors deal with the problem of extracting relations between entities from Wikipedia's En- glish articles, which can straightforwardly be transformed into Semantic Web meta data. Authors propose a method to exploit syntactic and [[semantic information]] for relation extraction. In addition, method can utilize the nature of Wikipedia to automatically obtain training data. The preliminary results of experiments strongly support hyperthesis that using information in higher level of description is better for relation extraction on Wikipedia and show that method is promising for text understanding.</div></td><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"><div>The exponential growth of [[Wikipedia]] recently attracts the attention of a large number of researchers and practitioners. One of the current challenge on Wikipedia is to make the encyclopedia processable for machines. In this paper, authors deal with the problem of extracting relations between entities from Wikipedia's En- glish articles, which can straightforwardly be transformed into Semantic Web meta data. Authors propose a method to exploit syntactic and [[semantic information]] for relation extraction. In addition, method can utilize the nature of Wikipedia to automatically obtain training data. The preliminary results of experiments strongly support hyperthesis that using information in higher level of description is better for relation extraction on Wikipedia and show that method is promising for text understanding.</div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;"></ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">== Embed ==</ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">=== Wikipedia Quality ===</ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;"><code></ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;"><nowiki></ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">Matsuo, Yutaka; Ishizuka, Mitsuru. (2006). "[[Exploiting Syntactic and Semantic Information for Relation Extraction from Wikipedia]]".</ins></div></td></tr>
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<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">=== English Wikipedia ===</ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;"><code></ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;"><nowiki></ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">{{cite journal |last1=Matsuo |first1=Yutaka |last2=Ishizuka |first2=Mitsuru |title=Exploiting Syntactic and Semantic Information for Relation Extraction from Wikipedia |date=2006 |url=https://wikipediaquality.com/wiki/Exploiting_Syntactic_and_Semantic_Information_for_Relation_Extraction_from_Wikipedia}}</ins></div></td></tr>
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<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;"></code></ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;"></ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">=== HTML ===</ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;"><code></ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;"><nowiki></ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">Matsuo, Yutaka; Ishizuka, Mitsuru. (2006). &amp;quot;<a href="https://wikipediaquality.com/wiki/Exploiting_Syntactic_and_Semantic_Information_for_Relation_Extraction_from_Wikipedia">Exploiting Syntactic and Semantic Information for Relation Extraction from Wikipedia</a>&amp;quot;.</ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;"></nowiki></ins></div></td></tr>
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</table>Madeleinehttps://wikipediaquality.com/index.php?title=Exploiting_Syntactic_and_Semantic_Information_for_Relation_Extraction_from_Wikipedia&diff=20088&oldid=prevLeah: infobox2019-08-09T19:50:20Z<p>infobox</p>
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<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">{{Infobox work</ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">| title = Exploiting Syntactic and Semantic Information for Relation Extraction from Wikipedia</ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">| date = 2006</ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">| authors = [[Yutaka Matsuo]]<br />[[Mitsuru Ishizuka]]</ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">| link = http://www.miv.t.u-tokyo.ac.jp/papers/dat-IJCAI07-TextLinkWS.pdf</ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">}}</ins></div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"><div>'''Exploiting Syntactic and Semantic Information for Relation Extraction from Wikipedia''' - scientific work related to [[Wikipedia quality]] published in 2006, written by [[Yutaka Matsuo]] and [[Mitsuru Ishizuka]].</div></td><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"><div>'''Exploiting Syntactic and Semantic Information for Relation Extraction from Wikipedia''' - scientific work related to [[Wikipedia quality]] published in 2006, written by [[Yutaka Matsuo]] and [[Mitsuru Ishizuka]].</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"></td><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"><div>== Overview ==</div></td><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"><div>== Overview ==</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"><div>The exponential growth of [[Wikipedia]] recently attracts the attention of a large number of researchers and practitioners. One of the current challenge on Wikipedia is to make the encyclopedia processable for machines. In this paper, authors deal with the problem of extracting relations between entities from Wikipedia's En- glish articles, which can straightforwardly be transformed into Semantic Web meta data. Authors propose a method to exploit syntactic and [[semantic information]] for relation extraction. In addition, method can utilize the nature of Wikipedia to automatically obtain training data. The preliminary results of experiments strongly support hyperthesis that using information in higher level of description is better for relation extraction on Wikipedia and show that method is promising for text understanding.</div></td><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"><div>The exponential growth of [[Wikipedia]] recently attracts the attention of a large number of researchers and practitioners. One of the current challenge on Wikipedia is to make the encyclopedia processable for machines. In this paper, authors deal with the problem of extracting relations between entities from Wikipedia's En- glish articles, which can straightforwardly be transformed into Semantic Web meta data. Authors propose a method to exploit syntactic and [[semantic information]] for relation extraction. In addition, method can utilize the nature of Wikipedia to automatically obtain training data. The preliminary results of experiments strongly support hyperthesis that using information in higher level of description is better for relation extraction on Wikipedia and show that method is promising for text understanding.</div></td></tr>
</table>Leahhttps://wikipediaquality.com/index.php?title=Exploiting_Syntactic_and_Semantic_Information_for_Relation_Extraction_from_Wikipedia&diff=20011&oldid=prevSofia: Adding wikilinks2019-08-06T04:53:30Z<p>Adding wikilinks</p>
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<tr><td class='diff-marker'>−</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>'''Exploiting Syntactic and Semantic Information for Relation Extraction from Wikipedia''' - scientific work related to Wikipedia quality published in 2006, written by Yutaka Matsuo and Mitsuru Ishizuka.</div></td><td class='diff-marker'>+</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>'''Exploiting Syntactic and Semantic Information for Relation Extraction from Wikipedia''' - scientific work related to <ins class="diffchange diffchange-inline">[[</ins>Wikipedia quality<ins class="diffchange diffchange-inline">]] </ins>published in 2006, written by <ins class="diffchange diffchange-inline">[[</ins>Yutaka Matsuo<ins class="diffchange diffchange-inline">]] </ins>and <ins class="diffchange diffchange-inline">[[</ins>Mitsuru Ishizuka<ins class="diffchange diffchange-inline">]]</ins>.</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"></td><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"><div>== Overview ==</div></td><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"><div>== Overview ==</div></td></tr>
<tr><td class='diff-marker'>−</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>The exponential growth of Wikipedia recently attracts the attention of a large number of researchers and practitioners. One of the current challenge on Wikipedia is to make the encyclopedia processable for machines. In this paper, authors deal with the problem of extracting relations between entities from Wikipedia's En- glish articles, which can straightforwardly be transformed into Semantic Web meta data. Authors propose a method to exploit syntactic and semantic information for relation extraction. In addition, method can utilize the nature of Wikipedia to automatically obtain training data. The preliminary results of experiments strongly support hyperthesis that using information in higher level of description is better for relation extraction on Wikipedia and show that method is promising for text understanding.</div></td><td class='diff-marker'>+</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>The exponential growth of <ins class="diffchange diffchange-inline">[[</ins>Wikipedia<ins class="diffchange diffchange-inline">]] </ins>recently attracts the attention of a large number of researchers and practitioners. One of the current challenge on Wikipedia is to make the encyclopedia processable for machines. In this paper, authors deal with the problem of extracting relations between entities from Wikipedia's En- glish articles, which can straightforwardly be transformed into Semantic Web meta data. Authors propose a method to exploit syntactic and <ins class="diffchange diffchange-inline">[[</ins>semantic information<ins class="diffchange diffchange-inline">]] </ins>for relation extraction. In addition, method can utilize the nature of Wikipedia to automatically obtain training data. The preliminary results of experiments strongly support hyperthesis that using information in higher level of description is better for relation extraction on Wikipedia and show that method is promising for text understanding.</div></td></tr>
</table>Sofiahttps://wikipediaquality.com/index.php?title=Exploiting_Syntactic_and_Semantic_Information_for_Relation_Extraction_from_Wikipedia&diff=17108&oldid=prevNaomi: Starting an article - Exploiting Syntactic and Semantic Information for Relation Extraction from Wikipedia2019-06-08T04:35:37Z<p>Starting an article - Exploiting Syntactic and Semantic Information for Relation Extraction from Wikipedia</p>
<p><b>New page</b></p><div>'''Exploiting Syntactic and Semantic Information for Relation Extraction from Wikipedia''' - scientific work related to Wikipedia quality published in 2006, written by Yutaka Matsuo and Mitsuru Ishizuka.<br />
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== Overview ==<br />
The exponential growth of Wikipedia recently attracts the attention of a large number of researchers and practitioners. One of the current challenge on Wikipedia is to make the encyclopedia processable for machines. In this paper, authors deal with the problem of extracting relations between entities from Wikipedia's En- glish articles, which can straightforwardly be transformed into Semantic Web meta data. Authors propose a method to exploit syntactic and semantic information for relation extraction. In addition, method can utilize the nature of Wikipedia to automatically obtain training data. The preliminary results of experiments strongly support hyperthesis that using information in higher level of description is better for relation extraction on Wikipedia and show that method is promising for text understanding.</div>Naomi