I use an algorithm to automatically convert a dependency treebank to a constituency treebank. These are two trees. The algorithm decomposes the dependency tree to a set of edges and for each edge find a corresponding sub-tree (these pairs could be given by the user or extracted from a treebank). Then glues these sub-trees to create the constituency tree.How do you define precision and recall for such an algorithm? or any other error measure?I just can figure out an error rate in which I count the correct conversions (at the tree level) divided by the total conversions made.
How to calculate precision and recall for treebank conversion
nlp