Abstract

We describe the NYU-CUBoulder systems for the SIGMORPHON 2020 Task 0 on typologically diverse morphological inflection and Task 2 on unsupervised morphological paradigm completion. The former consists of generating morphological inflections from a lemma and a set of morphosyntactic features describing the target form. The latter requires generating entire paradigms for a set of given lemmas from raw text alone. We model morphological inflection as a sequence-to-sequence problem, where the input is the sequence of the lemma’s characters with morphological tags, and the output is the sequence of the inflected form’s characters. First, we apply a transformer model to the task. Second, as inflected forms share most characters with the lemma, we further propose a pointer-generator transformer model to allow easy copying of input characters.

Highlights

  • IntroductionA word’s surface form reflects syntactic and semantic properties that are expressed by the word

  • In morphologically rich languages, a word’s surface form reflects syntactic and semantic properties that are expressed by the word

  • We presented the NYU-CUBoulder submissions for SIGMORPHON 2020 Task 0 and Task 2

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Summary

Introduction

A word’s surface form reflects syntactic and semantic properties that are expressed by the word. Others have many inflections per base form or lemma: a Polish verb has nearly 100 inflected forms (Janecki, 2000) and an Archi verb has around 1.5 million (Kibrik, 1998). Morphological inflection is the task of, given an input word – a lemma – together with morphosyntactic features defining the target form, gen-. V;3;SG;PRS seels erating the indicated inflected form, cf Figure 1. Morphological inflection is a useful tool for many natural language processing tasks (Seeker and Cetinoglu, 2015; Cotterell et al, 2016b), especially in morphologically rich languages where handling inflected forms can reduce data sparsity (Minkov et al, 2007)

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