Neural CRF Model for Sentence Alignment in Text Simplification
Table 3: Ablation study of our aligner on dev set.
['[EMPTY]', '[BOLD] Task 1  [BOLD] P', '[BOLD] Task 1  [BOLD] R', '[BOLD] Task 1  [BOLD] F1', '[BOLD] Task 2  [BOLD] P', '[BOLD] Task 2  [BOLD] R', '[BOLD] Task 2  [BOLD] F1']
Both accuracy and computing efficiency can be improved if we align paragraphs before aligning sentences. Moreover, aligning paragraphs first provides more training instances and reduces the label space for our neural CRF model. We analyze the design choices crucial for the good performance of our alignment model, namely CRF component, the paragraph alignment and the BERT-based semantic similarity measure.