CaMEL: Case Marker Extraction without Labels
Leonie Weissweiler, Valentin Hofmann, Masoud Jalili Sabet, Hinrich Schuetze
Abstract
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.
BibTeX
@inproceedings{weissweiler-etal-2022-camel,
title = "{CaMEL}: {C}ase {M}arker {E}xtraction without {L}abels",
author = "Weissweiler, Leonie and
Hofmann, Valentin and
Jalili Sabet, Masoud and
Schuetze, Hinrich",
editor = "Muresan, Smaranda and
Nakov, Preslav and
Villavicencio, Aline",
booktitle = "Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)",
month = may,
year = "2022",
address = "Dublin, Ireland",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2022.acl-long.377/",
doi = "10.18653/v1/2022.acl-long.377",
pages = "5506--5516"
}