Abstract
Given the fact that verbs play a crucial role in language comprehension, this paper presents a study which compares the verb senses in English PropBank with the ones in English WordNet through manual tagging. After analyzing 1554 senses in 1453 distinct verbs, we have found out that while the majority of the senses in PropBank have their one-to-one correspondents in WordNet, a substantial amount of them are differentiated. Furthermore, by analysing the differences between our manually-tagged and an automatically-tagged resource, we claim that manual tagging can help provide better results in sense annotation.- Anthology ID:
- 2019.gwc-1.39
- Volume:
- Proceedings of the 10th Global Wordnet Conference
- Month:
- July
- Year:
- 2019
- Address:
- Wroclaw, Poland
- Editors:
- Piek Vossen, Christiane Fellbaum
- Venue:
- GWC
- SIG:
- SIGLEX
- Publisher:
- Global Wordnet Association
- Note:
- Pages:
- 307–314
- Language:
- URL:
- https://aclanthology.org/2019.gwc-1.39
- DOI:
- Cite (ACL):
- Özge Bakay, Begüm Avar, and Olcay Taner Yıldız. 2019. Comparing Sense Categorization Between English PropBank and English WordNet. In Proceedings of the 10th Global Wordnet Conference, pages 307–314, Wroclaw, Poland. Global Wordnet Association.
- Cite (Informal):
- Comparing Sense Categorization Between English PropBank and English WordNet (Bakay et al., GWC 2019)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-1/2019.gwc-1.39.pdf
- Data
- FrameNet