On German verb sense disambiguation: A three-part approach based on linking a sense inventory (GermaNet) to a corpus through annotation (TGVCorp) and using the corpus to train a VSD classifier (TTvSense)

• Autorzy: Mattern, Dominik , Hemati, Wahed , Lücking, Andy , Mehler, Alexander
• Języki publikacji: EN

Abstrakty

EN

We develop a three-part approach to Verb Sense Disambiguation (VSD) in German. After considering a set of lexical resources and corpora, we arrive at a statistically motivated selection of a subset of verbs and their senses from GermaNet. This sub-inventory is then used to disambiguate the occurrences of the corresponding verbs in a corpus resulting from the union of TüBa-D/Z, Salsa, and E-VALBU. The corpus annotated in this way is called TGVCorp. It is used in the third part of the paper for training a classifier for VSD and for its comparative evaluation with a state-of-the-art approach in this research area, namely EWISER. Our simple classifier outperforms the transformer-based approach on the same data in both accuracy and speed in German but not in English and we discuss possible reasons.

Słowa kluczowe

EN

verb sense disambiguation; VSD; word sense disambiguation; WSD

• Czasopismo: Journal of Language Modelling
• Rocznik: 2024
• Tom: Vol. 12, No. 1
• Strony: 155--212
• Opis fizyczny: Bibliogr. 117 poz., rys., tab., wykr.

Twórcy

autor

Mattern, Dominik

• Goethe University Frankfurt, Text Technology Lab FrankfurtamMain,Germany

autor

Hemati, Wahed

• Shikenso GmbH FrankfurtamMain,Germany

autor

Lücking, Andy

• Goethe University Frankfurt, Text Technology Lab FrankfurtamMain,Germany

autor

Mehler, Alexander

• Goethe University Frankfurt, Text Technology Lab FrankfurtamMain,Germany,

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Identyfikatory

DOI

10.15398/jlm.v12i1.356