Data2Text Studio: Automated Text Generation from Structured Data

Longxu Dou, Guanghui Qin, Jinpeng Wang, Jin-Ge Yao, Chin-Yew Lin
2018 Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing: System Demonstrations  
Data2Text Studio is a platform for automated text generation from structured data. It is equipped with a Semi-HMMs model to extract high-quality templates and corresponding trigger conditions from parallel data automatically, which improves the interactivity and interpretability of the generated text. In addition, several easy-to-use tools are provided for developers to edit templates of pre-trained models, and APIs are released for developers to call the pre-trained model to generate texts in
more » ... hird-party applications. We conduct experiments on ROTOWIRE datasets for template extraction and text generation. The results show that our model achieves improvements on both tasks.
doi:10.18653/v1/d18-2003 dblp:conf/emnlp/DouQWYL18 fatcat:f7hqr5o3svde3lsjyxvjrytena