  News articles such as sports game reports are often thought to closely follow
the underlying game statistics, but in practice they contain a notable amount
of background knowledge, interpretation, insight into the game, and quotes that
are not present in the official statistics. This poses a challenge for
automated data-to-text news generation with real-world news corpora as training
data. We report on the development of a corpus of Finnish ice hockey news,
edited to be suitable for training of end-to-end news generation methods, as
well as demonstrate generation of text, which was judged by journalists to be
relatively close to a viable product. The new dataset and system source code
are available for research purposes at
https://github.com/scoopmatic/finnish-hockey-news-generation-paper.
