  We introduce CaMEL (Case Marker Extraction without Labels), a novel and
challenging task in computational morphology that is especially relevant for
low-resource languages. We propose a first model for CaMEL that uses a
massively multilingual corpus to extract case markers in 83 languages based
only on a noun phrase chunker and an alignment system. To evaluate CaMEL, we
automatically construct a silver standard from UniMorph. The case markers
extracted by our model can be used to detect and visualise similarities and
differences between the case systems of different languages as well as to
annotate fine-grained deep cases in languages in which they are not overtly
marked.
