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Multi-Team: A Multi-attention, Multi-decoder Approach to Morphological Analysis
2019
Proceedings of the 16th Workshop on Computational Research in Phonetics, Phonology, and Morphology
unpublished
This paper describes our submission to SIG-MORPHON 2019 Task 2: Morphological analysis and lemmatization in context. Our model is a multi-task sequence to sequence neural network, which jointly learns morphological tagging and lemmatization. On the encoding side, we exploit character-level as well as contextual information. We introduce a multi-attention decoder to selectively focus on different parts of character and word sequences. To further improve the model, we train on multiple datasets
doi:10.18653/v1/w19-4206
fatcat:g37ndtu5x5hfjdr3eofzjc5awy