CBNU System for SIGMORPHON 2019 Shared Task 2: a Pipeline Model

Uygun Shadikhodjaev, Jae Sung Lee


Abstract
In this paper we describe our system for morphological analysis and lemmatization in context, using a transformer-based sequence to sequence model and a biaffine attention based BiLSTM model. First, a lemma is produced for a given word, and then both the lemma and the given word are used for morphological analysis. We also make use of character level word encodings and trainable encodings to improve accuracy. Overall, our system ranked fifth in lemmatization and sixth in morphological accuracy among twelve systems, and demonstrated considerable improvements over the baseline in morphological analysis.
Anthology ID:
W19-4204
Volume:
Proceedings of the 16th Workshop on Computational Research in Phonetics, Phonology, and Morphology
Month:
August
Year:
2019
Address:
Florence, Italy
Venue:
ACL
SIG:
SIGMORPHON
Publisher:
Association for Computational Linguistics
Note:
Pages:
19–24
Language:
URL:
https://aclanthology.org/W19-4204
DOI:
10.18653/v1/W19-4204
Bibkey:
Cite (ACL):
Uygun Shadikhodjaev and Jae Sung Lee. 2019. CBNU System for SIGMORPHON 2019 Shared Task 2: a Pipeline Model. In Proceedings of the 16th Workshop on Computational Research in Phonetics, Phonology, and Morphology, pages 19–24, Florence, Italy. Association for Computational Linguistics.
Cite (Informal):
CBNU System for SIGMORPHON 2019 Shared Task 2: a Pipeline Model (Shadikhodjaev & Lee, ACL 2019)
Copy Citation:
PDF:
https://aclanthology.org/W19-4204.pdf
Data
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