# CMU-01 at the SIGMORPHON 2019 Shared Task on Crosslinguality and Context in Morphology

arXiv: https://arxiv.org/abs/1907.10129 · HTML: https://mlsanity.com/paper/1907.10129/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 23 Jul 2019.

## Built on by (most cited first, 1 of 1)

- [Understanding the effects of word-level linguistic annotations in under-resourced neural machine translation](https://mlsanity.com/paper/2401.16078/) (2024)

## Abstract (arXiv)

This paper presents the submission by the CMU-01 team to the SIGMORPHON 2019 task 2 of Morphological Analysis and Lemmatization in Context. This task requires us to produce the lemma and morpho-syntactic description of each token in a sequence, for 107 treebanks. We approach this task with a hierarchical neural conditional random field (CRF) model which predicts each coarse-grained feature (eg. POS, Case, etc.) independently. However, most treebanks are under-resourced, thus making it challenging to train deep neural models for them. Hence, we propose a multi-lingual transfer training regime where we transfer from multiple related languages that share similar typology.