We use Generalized Entity Matching (GEM) to satisfy these practical requirements and present an end-to-end pipeline, Machop, as the solution. Machop allows end users to define new matching tasks from scratch and apply them to new domains in a step-by-step manner. Machop casts the GEM problem as sequence pair classification so as to utilize the language understanding capability of Transformers-based language models (LMs) such as BERT.