Automated learning of templates for data-to-text generation: comparing rule-based, statistical and neural methods

WS 2018 Chris van der LeeEmiel KrahmerS Wubbener

The current study investigated novel techniques and methods for trainable approaches to data-to-text generation. Neural Machine Translation was explored for the conversion from data to text as well as the addition of extra templatization steps of the data input and text output in the conversion process... (read more)

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