5 research outputs found
Copenhagen at CoNLL--SIGMORPHON 2018: Multilingual Inflection in Context with Explicit Morphosyntactic Decoding
This paper documents the Team Copenhagen system which placed first in the
CoNLL--SIGMORPHON 2018 shared task on universal morphological reinflection,
Task 2 with an overall accuracy of 49.87. Task 2 focuses on morphological
inflection in context: generating an inflected word form, given the lemma of
the word and the context it occurs in. Previous SIGMORPHON shared tasks have
focused on context-agnostic inflection---the "inflection in context" task was
introduced this year. We approach this with an encoder-decoder architecture
over character sequences with three core innovations, all contributing to an
improvement in performance: (1) a wide context window; (2) a multi-task
learning approach with the auxiliary task of MSD prediction; (3) training
models in a multilingual fashion
PLPrepare: A Grammar Checker for Challenging Cases
This study investigates one of the Polish language’s most arbitrary cases: the genitive masculine inanimate singular. It collects and ranks several guidelines to help language learners discern its proper usage and also introduces a framework to provide detailed feedback regarding arbitrary cases. The study tests this framework by implementing and evaluating a hybrid grammar checker called PLPrepare. PLPrepare performs similarly to other grammar checkers and is able to detect genitive case usages and provide feedback based on a number of error classifications