Neural and Linear Pipeline Approaches to Cross-lingual Morphological Analysis

Çağrı Çöltekin, Jeremy Barnes


Abstract
This paper describes Tübingen-Oslo team’s participation in the cross-lingual morphological analysis task in the VarDial 2019 evaluation campaign. We participated in the shared task with a standard neural network model. Our model achieved analysis F1-scores of 31.48 and 23.67 on test languages Karachay-Balkar (Turkic) and Sardinian (Romance) respectively. The scores are comparable to the scores obtained by the other participants in both language families, and the analysis score on the Romance data set was also the best result obtained in the shared task. Besides describing the system used in our shared task participation, we describe another, simpler, model based on linear classifiers, and present further analyses using both models. Our analyses, besides revealing some of the difficult cases, also confirm that the usefulness of a source language in this task is highly correlated with the similarity of source and target languages.
Anthology ID:
W19-1416
Volume:
Proceedings of the Sixth Workshop on NLP for Similar Languages, Varieties and Dialects
Month:
June
Year:
2019
Address:
Ann Arbor, Michigan
Venues:
NAACL | VarDial | WS
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
153–164
Language:
URL:
https://aclanthology.org/W19-1416
DOI:
10.18653/v1/W19-1416
Bibkey:
Cite (ACL):
Çağrı Çöltekin and Jeremy Barnes. 2019. Neural and Linear Pipeline Approaches to Cross-lingual Morphological Analysis. In Proceedings of the Sixth Workshop on NLP for Similar Languages, Varieties and Dialects, pages 153–164, Ann Arbor, Michigan. Association for Computational Linguistics.
Cite (Informal):
Neural and Linear Pipeline Approaches to Cross-lingual Morphological Analysis (Çöltekin & Barnes, 2019)
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PDF:
https://aclanthology.org/W19-1416.pdf