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Finding hedges by chasing weasels: hedge detection using Wikipedia tags and shallow linguistic features
Abstract We investigate the automatic detection of We investigate the automatic detection of sentences containing linguistic hedges using corpus statistics and syntactic patterns. We take Wikipedia as an already annotated corpus using its tagged weasel words which mark sentences and phrases as non-factual. We evaluate the quality of Wikipedia as training data for hedge detection, as well as shallow linguistic features.n, as well as shallow linguistic features.
Added by wikilit team Added on initial load  +
Collected data time dimension Cross-sectional  +
Conclusion The experiments show that the syntactic paThe experiments show that the syntactic patterns work better when using a broader notion of hedging tested on manual annotations. When evaluating on Wikipedia weasel tags itself, word frequency and distance to the tag is sufficient. Our approach takes a much broader domain into account than previous work. It can also easily be applied to different languages as the weasel tag exists in more than 20 different language versions of Wikipedia. For a narrow domain, we suggest to start with our approach for deriving a seed set of hedging indicators and then to use a weakly supervised approach. Though our classifiers were trained on data from multiple Wikipedia dumps, there were only a few hundred training instances available. The transient nature of the weasel tag suggests to use the Wikipedia edit history for future work, since the edits faithfully record all occurrences of weasel tags.lly record all occurrences of weasel tags.
Data source Experiment responses  + , Wikipedia pages  +
Google scholar url http://scholar.google.com/scholar?ie=UTF-8&q=%22Finding%2Bhedges%2Bby%2Bchasing%2Bweasels%3A%2Bhedge%2Bdetection%2Busing%2BWikipedia%2Btags%2Band%2Bshallow%2Blinguistic%2Bfeatures%22  +
Has author Viola Ganter + , Michael Strube +
Has domain Computer science +
Has topic Computational linguistics +
Pages 173-176  +
Peer reviewed Yes  +
Publication type Conference paper  +
Published in ACLShort '09 Proceedings of the ACL-IJCNLP 2009 Conference Short Papers +
Research design Experiment  +
Research questions We investigate the automatic detection of We investigate the automatic detection of sentences containing linguistic hedges using corpus statistics and syntactic patterns. We take Wikipedia as an already annotated corpus using its tagged weasel words which mark sentences and phrases as non-factual. We evaluate the quality of Wikipedia as training data for hedge detection, as well as shallow linguistic features.n, as well as shallow linguistic features.
Revid 10,773  +
Theories Undetermined
Theory type Design and action  +
Title Finding hedges by chasing weasels: hedge detection using Wikipedia tags and shallow linguistic features
Unit of analysis Article  +
Url http://dl.acm.org/citation.cfm?id=1667636  +
Wikipedia coverage Main topic  +
Wikipedia data extraction Dump  +
Wikipedia language Not specified  +
Wikipedia page type Article  +
Year 2009  +
Creation dateThis property is a special property in this wiki. 15 March 2012 20:28:23  +
Categories Computational linguistics  + , Computer science  + , Publications with missing comments  + , Publications  +
Modification dateThis property is a special property in this wiki. 30 January 2014 20:27:44  +
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