Experiments on morphological reinflection: Conll 2018 shared task

Abstract

We present a system for the task of morphological inflection, i.e., finding a target morphological form, given a lemma and a set of target tags. System is trained on datasets of three sizes: low, medium and high. The system uses a simple Long Short-Term Memory (LSTM) based encoder-decoder based model. The performance for low size dataset is poor in general while it improves significantly for medium and high sized training dataset. The average performance over all languages is poor as compared to baseline for low dataset, it is comparable for medium dataset, and significantly more for high dataset. © 2018 Association for Computational Linguistics.