TabGenie: A Toolkit for Table-to-Text Generation

Heterogenity of data-to-text generation datasets limits the research on data-to-text generation systems. We present TABGENIE -a toolkit which enables researchers to explore, preprocess, and analyze a variety of data-to-text generation datasets through the unified framework of table-to-text generation. In TABGENIE, all inputs are represented as tables with associated metadata. The tables can be explored through a web interface, which also provides an interactive mode for debugging table-to-text generation, facilitates side-by-side comparison of generated system outputs, and allows easy exports for manual analysis. Furthermore, TAB-GENIE is equipped with command line processing tools and Python bindings for unified dataset loading and processing. We release TABGENIE as a PyPI package 1 and provide its open-source code and a live demo at https: //github.com/kasnerz/tabgenie .