Error Analysis for Vietnamese Dependency Parsing
Table VII: Dependency arc precisions/recalls relative to predicted/gold siblings. NMS = Number of Modifier Siblings; PER = Percentage.
['[BOLD] NMS', '[BOLD] PER', '[BOLD] Precision  [BOLD] MST', '[BOLD] Precision  [BOLD] Malt', '[BOLD] Precision Δ', '[BOLD] Recall  [BOLD] MST', '[BOLD] Recall  [BOLD] Malt', '[BOLD] Recall Δ']
The second graph property we examine is the sibling of arcs. We want to quantify the local neighborhood of an arc within a dependency graph. In general, both of parsers have low precisions and recalls, and tend to be more precise for those arcs with fewer siblings. MSTParser performs better for dependency arcs that have no siblings ( dependency relations containing dependent is leaf), whereas MaltParser tends to be more accurate for those arcs with more siblings. When a sentence has more siblings, it generates more long-distance dependencies. These results are consistent with the previous analysis results.