They argued that the top terms in claim vs. nonclaim sentences are highly overlapping in content, which is a problem for bag-of-words approaches.
they used a Convolutional Neural Network, where each word is represented by its embedding and each named entity is replaced by its tag, e.g., person, organization, location.