This paper describes the SEMAFOR system’s performance in the SemEval 2010
task on linking events and their participants in discourse. Our entry is based
upon SEMAFOR 1.0 (Das et al., 2010a),
a frame-semantic probabilistic parser built
from log-linear models. The extended system models null instantiations, including
non-local argument reference. Performance
is evaluated on the task data with and without gold-standard overt arguments. In both
settings, it fares the best of the submitted
systems with respect to recall and F1.

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