Selecting, Planning, and Rewriting: A Modular Approach for Data-to-Document Generation and Translation
Lesly Miculicich, Marc Marone, Hany Hassan · 2019
In this paper, we report our system submissions to all 6 tracks of the WNGT 2019 shared task on Document-Level Generation and Translation.The objective is to generate a textual document from either structured data: generation task, or a document in a different language: translation task.For the translation task, we focused on adapting a large scale system trained on WMT data by fine tuning it on the RotoWire data.For the generation task, we participated with two systems based on a selection and planning model followed by (a) a simple language model generation, and (b) a GPT-2 pre-trained language model approach.The selection and planning module chooses a subset of table records in order, and the language models produce text given such a subset.