Abstract
Morphological tasks have gained decent popularity within the NLP community in the recent years, with large multi-lingual datasets providing morphological analysis of words, either in or out of context. However, the lack of a clear linguistic definition for words destines the annotative work to be incomplete and mired in inconsistencies, especially cross-linguistically. In this work we expand morphological inflection of words to inflection of sentences to provide true universality disconnected from orthographic traditions of white-space usage. To allow annotation for sentence-inflection we define a morphological annotation scheme by a fixed set of inflectional features. We present a small cross-linguistic dataset including semi-manually generated simple sentences in 4 typologically diverse languages annotated according to our suggested scheme, and show that the task of reinflection gets substantially more difficult but that the change of scope from words to well-defined sentences allows interface with contextualized language models.- Anthology ID:
- 2021.mrl-1.23
- Volume:
- Proceedings of the 1st Workshop on Multilingual Representation Learning
- Month:
- November
- Year:
- 2021
- Address:
- Punta Cana, Dominican Republic
- Editors:
- Duygu Ataman, Alexandra Birch, Alexis Conneau, Orhan Firat, Sebastian Ruder, Gozde Gul Sahin
- Venue:
- MRL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 248–250
- Language:
- URL:
- https://aclanthology.org/2021.mrl-1.23
- DOI:
- 10.18653/v1/2021.mrl-1.23
- Cite (ACL):
- Omer Goldman and Reut Tsarfaty. 2021. Well-Defined Morphology is Sentence-Level Morphology. In Proceedings of the 1st Workshop on Multilingual Representation Learning, pages 248–250, Punta Cana, Dominican Republic. Association for Computational Linguistics.
- Cite (Informal):
- Well-Defined Morphology is Sentence-Level Morphology (Goldman & Tsarfaty, MRL 2021)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-4/2021.mrl-1.23.pdf