The article explores how filtering out less important sentences from news broadcasts can improve the accuracy of extracting key phrases. By removing just 10% of sentences, the precision and recall of key phrase extraction increased by 2%. The researchers used a toolkit called MAUI and a supervised learning approach to train and test their method on a gold standard of news stories. The experiments were conducted within a system that monitors TV and radio news channels daily.