  Existing multiparty dialogue datasets for entity coreference resolution are
nascent, and many challenges are still unaddressed. We create a large-scale
dataset, Multilingual Multiparty Coref (MMC), for this task based on TV
transcripts. Due to the availability of gold-quality subtitles in multiple
languages, we propose reusing the annotations to create silver coreference
resolution data in other languages (Chinese and Farsi) via annotation
projection. On the gold (English) data, off-the-shelf models perform relatively
poorly on MMC, suggesting that MMC has broader coverage of multiparty
coreference than prior datasets. On the silver data, we find success both using
it for data augmentation and training from scratch, which effectively simulates
the zero-shot cross-lingual setting.
