Performance values for models that use combinations of text, positional and linkage features.

Values calculated across the whole-corpus as well as per-article averages are shown. Each row gives the performance measures for one model. The T, P and L columns indicate with a those models that use text, positional, and linkage features, respectively. The sentences-in-states CRF approach, CRF (SIS), has the top performance on all measures. Asterisks denote -values (*denotes and **denotes ) from paired -tests comparing the per-article performance of our methods to those of Baseline+DM, the current state-of-the-art.本研究展示了全语料库层面及单篇文章平均维度下计算得到的各项指标值。每一行对应单个模型的性能评估指标。T、P、L三列分别标注了采用文本特征、位置特征与关联特征的模型。基于状态句的条件随机场（CRF (SIS)）方法在所有评估指标上均取得最优性能。星号代表配对t检验得到的显著性p值，其中*代表原文未明确标注的显著性水平，**同样代表原文未明确标注的显著性水平，本研究通过该检验对比了所提方法与当前最优基线模型Baseline+DM的单篇文章性能表现。