A BiLSTM plus Turkish BERT lemmatizer and morphological tagger is tested on IMST and PUD, beating SIGMORPHON 2019 on most metrics but not on PUD lemmatization accuracy, while the paper's claim of being the first context-aware Turkish lemmatizer is contradicted by its own citations.
The SIGMORPHON 2019 Shared Task: Morphological Analysis in Context and Cross-Lingual Transfer for Inflection
1 Pith paper cite this work. Polarity classification is still indexing.
abstract
The SIGMORPHON 2019 shared task on cross-lingual transfer and contextual analysis in morphology examined transfer learning of inflection between 100 language pairs, as well as contextual lemmatization and morphosyntactic description in 66 languages. The first task evolves past years' inflection tasks by examining transfer of morphological inflection knowledge from a high-resource language to a low-resource language. This year also presents a new second challenge on lemmatization and morphological feature analysis in context. All submissions featured a neural component and built on either this year's strong baselines or highly ranked systems from previous years' shared tasks. Every participating team improved in accuracy over the baselines for the inflection task (though not Levenshtein distance), and every team in the contextual analysis task improved on both state-of-the-art neural and non-neural baselines.
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Context Aware Lemmatization and Morphological Tagging Method in Turkish
A BiLSTM plus Turkish BERT lemmatizer and morphological tagger is tested on IMST and PUD, beating SIGMORPHON 2019 on most metrics but not on PUD lemmatization accuracy, while the paper's claim of being the first context-aware Turkish lemmatizer is contradicted by its own citations.