Lexicon Infused Phrase Embeddings for Named Entity Resolution
Table 3: Final NER F1 scores for Ontonotes 5.0 dataset. The results in bold face are the best on each evaluation set.
['[BOLD] System', '[BOLD] Dev', '[BOLD] Test']
We found that both Skip-gram and Lexicon infused embeddings give better results than using Brown Clusters as features. However, in this case Skip-gram embeddings give marginally better results. (So as not to jeopardize our ability to fairly do further research on this task, we did not analyze the test set errors that may explain this.) These are, to the best of our knowledge, the first published performance numbers on the Ontonotes NER task.