Papers by Neslihan Cesur

1 papers
A Learning-Based Dependency to Constituency Conversion Algorithm for the Turkish Language (2022.lrec-1)

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Challenge: a team of linguists manually annotated a set of constituency trees.
Approach: They propose to create the first Turkish-based dependency-to-constituency conversion algorithm using a morphologic analyser and feature-based machine learning model.
Outcome: The proposed algorithm can be used to generate new constituency treebanks and training data for NLP resources like constituency parsers.

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