A Model-driven approach to NLP programming with UIMA.

In Natural Language Processing, more complex business use cases and shorter delivery times drive a growing need of smoother, more flexible and faster implementations. This trend also requires integrating and orchestrating different functionalities delivered by services belonging to different technological platforms. All these needs imply raising the level of abstraction for NLP components development. In this paper we present a Model Driven Architecture approach suitable to develop an open and interoperable UIMA-based NLP stack. By decoupling UIMA NLP models from other solution specific platforms and services, we obtain major architectural improvements.