  Human trafficking is a challenging law enforcement problem, and a large
amount of such activity manifests itself on various online forums. Given the
large, heterogeneous and noisy structure of this data, building models to
predict instances of trafficking is an even more convolved a task. In this
paper we propose and entity resolution pipeline using a notion of proxy labels,
in order to extract clusters from this data with prior history of human
trafficking activity. We apply this pipeline to 5M records from backpage.com
and report on the performance of this approach, challenges in terms of
scalability, and some significant domain specific characteristics of our
resolved entities.
