In contrast, the linear-chain models fail to exploit the sequential dependencies between nearby answer labels to improve the results significantly: although the labels from the neighboring answers can affect the label of the current answer, this dependency is too loose to have impact on the selection accuracy.
labels should be used together with answers' content to account for stronger and more effective dependencies.