Instructions: In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.
Input: In this work, we evaluate three publicly-available off-the-shelf coreference resolution systems, representing three different machine learning paradigms: rule-based systems, feature-driven statistical systems, and neural systems. We evaluate examples of each of the three coreference system architectures described in "Coreference Systems" : the BIBREF5 sieve system from the rule-based paradigm (referred to as RULE), BIBREF6 from the statistical paradigm (STAT), and the BIBREF11 deep reinforcement system from the neural paradigm (NEURAL).
Question: Which coreference resolution systems are tested?
Output:
the BIBREF5 sieve system from the rule-based paradigm (referred to as RULE), BIBREF6 from the statistical paradigm (STAT), and the BIBREF11 deep reinforcement system from the neural paradigm (NEURAL).