Greedy, Joint Syntactic-Semantic Parsing with Stack LSTMs
Table 4: Comparison of macro F1 scores on the multilingual CoNLL 2009 test set.
['Language', '#1 C+’09', '#2 Z+ ’09a', '#3 G+ ’09', 'Joint']
Multilingual We tested the joint model on the non-English CoNLL 2009 datasets, and the results demonstrate that it adapts easily—it is on par with the top three systems in most cases. We note that our Chinese parser relies on pretrained word embeddings for its superior performance; without them (not shown), it was on par with the others. Japanese is a small-data case (4,393 training examples), illustrating our model’s dependence on reasonably large training datasets.