https://wiki.apertium.org/w/index.php?title=Learning_Constraint_Grammars&feed=atom&action=history
Learning Constraint Grammars - Revision history
2024-03-28T19:45:30Z
Revision history for this page on the wiki
MediaWiki 1.34.1
https://wiki.apertium.org/w/index.php?title=Learning_Constraint_Grammars&diff=60924&oldid=prev
Nuboro at 22:59, 25 December 2016
2016-12-25T22:59:44Z
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<td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td>
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<td style="color: #222; 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>In statistical approach Constraint Grammar style rules are learned by calculating n-gram probabilities of word and part-of-speech tag groups. Current work on implementing such a system is at [https://github.com/nuboro/<del class="diffchange diffchange-inline">CG_module/</del> nuboro's Github repository], and it is based on the paper [https://archive.org/details/arxiv-cmp-lg9607002 Inducing Constraint Grammars].</div></td>
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<td style="color: #222; 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>In statistical approach Constraint Grammar style rules are learned by calculating n-gram probabilities of word and part-of-speech tag groups. Current work on implementing such a system is at [https://github.com/nuboro/<ins class="diffchange diffchange-inline">CG-generator</ins> nuboro's Github repository], and it is based on the paper [https://archive.org/details/arxiv-cmp-lg9607002 Inducing Constraint Grammars].</div></td>
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<td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td>
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Nuboro
https://wiki.apertium.org/w/index.php?title=Learning_Constraint_Grammars&diff=60886&oldid=prev
Putti at 12:39, 22 December 2016
2016-12-22T12:39:16Z
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<td colspan="2" style="background-color: #fff; color: #222; text-align: center;">Revision as of 12:39, 22 December 2016</td>
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<td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* http://swarm.cs.pub.ro/~asfrent/msc/thesis.pdf – Inductive Logic Programming</div></td>
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<td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* http://swarm.cs.pub.ro/~asfrent/msc/thesis.pdf – Inductive Logic Programming</div></td>
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<td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* http://ucrel.lancs.ac.uk/acl/C/C98/C98-2123.pdf – Inductive Logic Programming</div></td>
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<td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* http://ucrel.lancs.ac.uk/acl/C/C98/C98-2123.pdf – Inductive Logic Programming</div></td>
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<td style="color: #222; 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;"></td>
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Putti
https://wiki.apertium.org/w/index.php?title=Learning_Constraint_Grammars&diff=60885&oldid=prev
Putti at 12:27, 22 December 2016
2016-12-22T12:27:37Z
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<td colspan="2" style="background-color: #fff; color: #222; text-align: center;">Revision as of 12:27, 22 December 2016</td>
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<td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>A subfield of Machine Learning, called Inductive Logic Programming, has been used to learn Constraint Grammar style disambiguation rules. See for example the branch [http://svn.code.sf.net/p/apertium/svn/branches/mil-pos-tagger/ mil-pos-tagger].</div></td>
<td class="diff-marker"> </td>
<td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>A subfield of Machine Learning, called Inductive Logic Programming, has been used to learn Constraint Grammar style disambiguation rules. See for example the branch [http://svn.code.sf.net/p/apertium/svn/branches/mil-pos-tagger/ mil-pos-tagger].</div></td>
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<td style="color: #222; 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>==<del class="diffchange diffchange-inline">External links</del>==</div></td>
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<td style="color: #222; 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 class="diffchange diffchange-inline">Papers</ins>==</div></td>
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<td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* http://swarm.cs.pub.ro/~asfrent/msc/thesis.pdf – Inductive Logic Programming</div></td>
<td class="diff-marker"> </td>
<td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* http://swarm.cs.pub.ro/~asfrent/msc/thesis.pdf – Inductive Logic Programming</div></td>
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<td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* http://ucrel.lancs.ac.uk/acl/C/C98/C98-2123.pdf – Inductive Logic Programming</div></td>
<td class="diff-marker"> </td>
<td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* http://ucrel.lancs.ac.uk/acl/C/C98/C98-2123.pdf – Inductive Logic Programming</div></td>
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Putti
https://wiki.apertium.org/w/index.php?title=Learning_Constraint_Grammars&diff=60884&oldid=prev
Putti at 12:25, 22 December 2016
2016-12-22T12:25:46Z
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<td colspan="2" style="background-color: #fff; color: #222; text-align: center;">Revision as of 12:25, 22 December 2016</td>
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<td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>== Machine Learning ==</div></td>
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<td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>== Machine Learning ==</div></td>
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<td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td>
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<td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td>
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<td style="color: #222; 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>A subfield of Machine Learning, called Inductive Logic Programming, has been used to learn Constraint Grammar style disambiguation rules. See for example the branch [http://svn.code.sf.net/p/apertium/svn/branches/mil-pos-tagger/ mil-pos-tagger]</div></td>
<td class="diff-marker">+</td>
<td style="color: #222; 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>A subfield of Machine Learning, called Inductive Logic Programming, has been used to learn Constraint Grammar style disambiguation rules. See for example the branch [http://svn.code.sf.net/p/apertium/svn/branches/mil-pos-tagger/ mil-pos-tagger]<ins class="diffchange diffchange-inline">.</ins></div></td>
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<td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>==External links==</div></td>
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<td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>==External links==</div></td>
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Putti
https://wiki.apertium.org/w/index.php?title=Learning_Constraint_Grammars&diff=60883&oldid=prev
Putti at 12:25, 22 December 2016
2016-12-22T12:25:16Z
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<td colspan="2" style="background-color: #fff; color: #222; text-align: center;">Revision as of 12:25, 22 December 2016</td>
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<td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td>
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<td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td>
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<td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>A subfield of Machine Learning, called Inductive Logic Programming, has been used to learn Constraint Grammar style disambiguation rules. See for example the branch [http://svn.code.sf.net/p/apertium/svn/branches/mil-pos-tagger/ mil-pos-tagger]</div></td>
<td class="diff-marker"> </td>
<td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>A subfield of Machine Learning, called Inductive Logic Programming, has been used to learn Constraint Grammar style disambiguation rules. See for example the branch [http://svn.code.sf.net/p/apertium/svn/branches/mil-pos-tagger/ mil-pos-tagger]</div></td>
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<td style="color: #222; 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>==External links==</div></td>
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<td style="color: #222; 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>* http://swarm.cs.pub.ro/~asfrent/msc/thesis.pdf – Inductive Logic Programming</div></td>
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<td style="color: #222; 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>* http://ucrel.lancs.ac.uk/acl/C/C98/C98-2123.pdf – Inductive Logic Programming</div></td>
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Putti
https://wiki.apertium.org/w/index.php?title=Learning_Constraint_Grammars&diff=60882&oldid=prev
Putti at 12:15, 22 December 2016
2016-12-22T12:15:05Z
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<td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td>
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<td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>In statistical approach Constraint Grammar style rules are learned by calculating n-gram probabilities of word and part-of-speech tag groups. Current work on implementing such a system is at [https://github.com/nuboro/CG_module/ nuboro's Github repository], and it is based on the paper [https://archive.org/details/arxiv-cmp-lg9607002 Inducing Constraint Grammars].</div></td>
<td class="diff-marker"> </td>
<td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>In statistical approach Constraint Grammar style rules are learned by calculating n-gram probabilities of word and part-of-speech tag groups. Current work on implementing such a system is at [https://github.com/nuboro/CG_module/ nuboro's Github repository], and it is based on the paper [https://archive.org/details/arxiv-cmp-lg9607002 Inducing Constraint Grammars].</div></td>
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<td style="color: #222; 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>A subfield of Machine Learning, called Inductive Logic Programming, has been used to learn Constraint Grammar style disambiguation rules. See for example the branch [http://svn.code.sf.net/p/apertium/svn/branches/mil-pos-tagger/ mil-pos-tagger]</div></td>
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https://wiki.apertium.org/w/index.php?title=Learning_Constraint_Grammars&diff=60876&oldid=prev
Putti: Created page with "Constraint Grammar style part-of-speech disambiguation rules can be learned automatically from disambiguated parallel corpora. == Statistical approach == In statistical app..."
2016-12-22T11:51:22Z
<p>Created page with "Constraint Grammar style part-of-speech disambiguation rules can be learned automatically from disambiguated parallel corpora. == Statistical approach == In statistical app..."</p>
<p><b>New page</b></p><div>Constraint Grammar style part-of-speech disambiguation rules can be learned automatically from disambiguated parallel corpora.<br />
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== Statistical approach ==<br />
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In statistical approach Constraint Grammar style rules are learned by calculating n-gram probabilities of word and part-of-speech tag groups. Current work on implementing such a system is at [https://github.com/nuboro/CG_module/ nuboro's Github repository], and it is based on the paper [https://archive.org/details/arxiv-cmp-lg9607002 Inducing Constraint Grammars].</div>
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