  We present the first large scale corpus for entity resolution in email
conversations (CEREC). The corpus consists of 6001 email threads from the Enron
Email Corpus containing 36,448 email messages and 60,383 entity coreference
chains. The annotation is carried out as a two-step process with minimal manual
effort. Experiments are carried out for evaluating different features and
performance of four baselines on the created corpus. For the task of mention
identification and coreference resolution, a best performance of 59.2 F1 is
reported, highlighting the room for improvement. An in-depth qualitative and
quantitative error analysis is presented to understand the limitations of the
baselines considered.
