Zero-Shot Transfer Learning for Event Extraction
Table 3: Seen Types in Each Experiment Setting.
['Setting', 'N', 'Seen Types for Training/Dev']
We first use ACE event schema as our target event ontology and assume the boundaries of triggers and arguments are given. Of the 33 ACE event types, we select the top-N most popular event types from ACE05 data as “seen” types, and use 90% event annotations of these for training and 10% for development. N is set as 1, 3, 5, 10 respectively. We test the zero-shot classification performances on the annotations for the remaining 23 unseen types.