Working Hard or Hardly Working:Challenges of Integrating Typology into Neural Dependency Parsers
Table 4: Precision@k for identifying the best parsing transfer language, for the k typological neighbors.
['[EMPTY]', 'P@1', 'P@3', 'P@5', 'P@10']
Typology vs. Parser Transferability: The implicit assumption of all the typology based methods is that the typological similarity of two languages is a good indicator of their parsing transferability. As a measure of parser transferability, for each language we select the oracle source language which results in the best transfer performance. We then compute precision@k for the nearest k neighbors in the typological space, i.e. whether the best source appears in the k nearest neighbors. TD has the best alignment, which is consistent with its corresponding best parsing performance. Overall, this divergence motivates the development of approaches that better match the two distributions. We use Euclidean distance as our metric, another extreme simplification.