Resources for Modeling Derivation Using Methods from Distributional Semantics

Resources for the paper 'Predictability of Distributional Semantics in Derivational Word Formation'

Resources for Modeling Derivation Using Methods from Distributional Semantics

Typ
ExperimentData
Autor
Sebastian Padó, Aurélie Herbelot, Max Kisselew, Jan Šnajder

We are interested in modeling and investigating morphological derivation using methods from Distributional Semantics. Most our work for German is based on DErivBase (Zeller et al., 2013), a derivation lexicon that groups 280K lemmas into 17K derivational families. Other resources used in our recent work can be found below in the "Download" section.

Referenz

Sebastian Padó, Aurélie Herbelot, Max Kisselew, Jan Šnajder:
Predictability of Distributional Semantics in Derivational Word Formation.
In: Proceedings of COLING 2016. Osaka, Japan.

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Resources from Predictability of Distributional Semantics in Derivational Word Formation:

 

Sebastian Padó
Prof. Dr.

Sebastian Padó

Lehrstuhlinhaber Theoretische Computerlinguistik

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