  This paper presents a new natural language processing task - Actionable
Entities Recognition (AER) - recognition of entities that protagonists could
interact with for further plot development. Though similar to classical Named
Entity Recognition (NER), it has profound differences. In particular, it is
crucial for interactive fiction, where the agent needs to detect entities that
might be useful in the future. We also discuss if AER might be further helpful
for the systems dealing with narrative processing since actionable entities
profoundly impact the causal relationship in a story. We validate the proposed
task on two previously available datasets and present a new benchmark dataset
for the AER task that includes 5550 descriptions with one or more actionable
entities.
