Typical Sentences as a Resource for Valence

Uwe Quasthoff, Lars Hellan, Erik Körner, Thomas Eckart, Dirk Goldhahn, Dorothee Beermann


Abstract
Verb valence information can be derived from corpora by using subcorpora of typical sentences that are constructed in a language independent manner based on frequent POS structures. The inspection of typical sentences with a fixed verb in a certain position can show the valence information directly. Using verb fingerprints, consisting of the most typical sentence patterns the verb appears in, we are able to identify standard valence patterns and compare them against a language’s valence profile. With a very limited number of training data per language, valence information for other verbs can be derived as well. Based on the Norwegian valence patterns we are able to find comparative patterns in German where typical sentences are able to express the same situation in an equivalent way and can so construct verb valence pairs for a bilingual PolyVal dictionary. This contribution discusses this application with a focus on the Norwegian valence dictionary NorVal.
Anthology ID:
2020.lrec-1.649
Volume:
Proceedings of the Twelfth Language Resources and Evaluation Conference
Month:
May
Year:
2020
Address:
Marseille, France
Editors:
Nicoletta Calzolari, Frédéric Béchet, Philippe Blache, Khalid Choukri, Christopher Cieri, Thierry Declerck, Sara Goggi, Hitoshi Isahara, Bente Maegaard, Joseph Mariani, Hélène Mazo, Asuncion Moreno, Jan Odijk, Stelios Piperidis
Venue:
LREC
SIG:
Publisher:
European Language Resources Association
Note:
Pages:
5276–5281
Language:
English
URL:
https://aclanthology.org/2020.lrec-1.649
DOI:
Bibkey:
Cite (ACL):
Uwe Quasthoff, Lars Hellan, Erik Körner, Thomas Eckart, Dirk Goldhahn, and Dorothee Beermann. 2020. Typical Sentences as a Resource for Valence. In Proceedings of the Twelfth Language Resources and Evaluation Conference, pages 5276–5281, Marseille, France. European Language Resources Association.
Cite (Informal):
Typical Sentences as a Resource for Valence (Quasthoff et al., LREC 2020)
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PDF:
https://aclanthology.org/2020.lrec-1.649.pdf