Difference between revisions of "Linearizing Dependency Trees"
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The second data set will be a subset of the English Gigaword corpus, also parsed with the Stanford dependency parser. | The second data set will be a subset of the English Gigaword corpus, also parsed with the Stanford dependency parser. | ||
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| + | '''The Team''' | ||
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| + | This is a one-man team consisting of [[User:Jmflanig| Jeff Flanigan]]. | ||
Revision as of 01:23, 13 September 2011
The task
Given a set of dependencies between words in a sentence, predict the linear sequence of words. This is the inverse problem of dependency parsing, where a sequence of words is given and the dependencies are found.
The dataset
There will be two datasets.
The first dataset is the English side of the FBIS Chinese-English dataset, parsed with the Stanford dependency parser. One thousand lines will be held-out during training for evaluation.
The second data set will be a subset of the English Gigaword corpus, also parsed with the Stanford dependency parser.
The Team
This is a one-man team consisting of Jeff Flanigan.
