''You should probably read this'': Hedge Detection in Text
This work addresses the problem of identifying confidence levels in statements for domains like medicine and finance, but it is incremental as it builds on existing methods.
The paper tackled hedge detection in text by applying a joint model using words and part-of-speech tags, achieving a new top score on the CoNLL-2010 Wikipedia corpus.
Humans express ideas, beliefs, and statements through language. The manner of expression can carry information indicating the author's degree of confidence in their statement. Understanding the certainty level of a claim is crucial in areas such as medicine, finance, engineering, and many others where errors can lead to disastrous results. In this work, we apply a joint model that leverages words and part-of-speech tags to improve hedge detection in text and achieve a new top score on the CoNLL-2010 Wikipedia corpus.