Integrating Turkish Wordnet KeNet to Princeton WordNet: The Case of One-to-Many Correspondences

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Building the Turkish FrameNet (2021, methodology): “Following the footsteps of French FrameNet, we took a closer look at Turkish WordNet and designated 8 domains that would possibly contain the most frequent predicates in Turkish: Activity, Cause, Change, Motion, Cognition, Perception, Judgement and Commerce.”
Resources for Turkish natural language processing: A critical survey (2022, methodology): “This is partially improved by Bakay et al. (2019) who match 4417 of most frequent English senses from Princeton WordNet to KeNet synsets.”
A Semi-Automated Approach to the Annotation of Argument Structures in Turkish Datasets (2025, unknown): “0 is that its predicate-argument structures are based not on individual verbs but on the synsets defined in Turkish WordNet (Ehsani et al., 2018; Bakay et al., 2019).”
Turkish WordNet KeNet (2021, methodology): “There were three main reasons for the wrong mergings: meaning-related drifts, POS-related drifts and morphology-related problems (Bakay et al., 2019c).”
From Dependency to CCG to Incremental CCG: Approaches to Flexible Word Order in Turkish (2026, unknown): “Our primary dataset, used for the development of induced categories and the evaluation of CCG derivations, is the KeNet Word-Net corpus (Bakay et al., 2019a,b, 2021).”