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TweeboParser and Tweebank
We provide a dependency parser for English tweets, TweeboParser . The parseris trained on a subset of a new labeled corpus for 929 tweets (12,318 tokens) drawn from the POS-tagged tweetcorpus of Owoputi et al. (2013) , Tweebank .
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These were created byLingpeng Kong,Nathan Schneider,Swabha Swayamdipta,Archna Bhatia, Chris Dyer,and Noah A. Smith.
Thanks to Tweebank annotators:Waleed Ammar,Jason Baldridge,David Bamman, Dallas Card,Shay Cohen,Jesse Dodge,Jeffrey Flanigan,Dan Garrette,Lori Levin,Wang Ling, Bill McDowell,Michael Mordowanec,Brendan O’Connor,Rohan Ramanath,Yanchuan Sim,Liang Sun,Sam Thomson,and Dani Yogatama.
What TweeboParser does
Given a tweet, TweeboParser predicts its syntactic structure, represented by unlabeled dependencies.Since a tweet often contains more than one utterance, the output of TweeboParser will often be a multi-rooted graph over the tweet. Also, many elements in tweets have no syntactic function. These include, in many cases, hashtags, URLs, and emoticons. TweeboParser tries to exclude thesetokens from the parse tree (grayed out in the example below).
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Please refer to the paper for more information.
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An example of a dependency parse of a tweet is:Corresponding CoNLL format representation of the dependency tree above:
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