In this paper we describe our system and experimental results on the development set of the Surface Realisation Shared Task. Our system is an entry for the Shallow-Task, with two different models based on deep-learning implementations for building the sentence combined with a rule-based morphology component.

We present a readily available API that solves the morphology component for surface realizers in 10 languages (e.g., English, German and Finnish) for any topic and is available as REST API. This can be used to add morphology to any kind of NLG application (e.g., a multi-language chatbot), without requiring computational linguistic knowledge by the integrator.