# CaMEL: Case Marker Extraction without Labels

Source: [CaMEL: Case Marker Extraction without Labels](<https://www.sota2.com/research/paper/68fa6c1b1e209131cea323a3>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2026-01-04T05:09:42.165Z

Authors: Leonie Weissweiler, Valentin Hofmann, Masoud Jalili Sabet, Hinrich Sch\\"utze

Published: 2022-03-18T15:20:14.000Z

## 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.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

- [Case Marker Extraction on Silver Standard](<https://www.sota2.com/research/sota/case-marker-extraction-on-silver-standard.md>): Case Marker Extraction; Silver Standard; Precision: 83.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/2203.10010>)

[PDF](<https://arxiv.org/pdf/2203.10010.pdf>)

[Implementation](<https://github.com/LeonieWeissweiler/CaMEL>)