Abstract
This paper presents the first investigation on using semantic frames to assess text difficulty. Based on Mandarin VerbNet, a verbal semantic database that adopts a frame-based approach, we examine usage patterns of ten verbs in a corpus of graded Chinese texts. We identify a number of characteristics in texts at advanced grades: more frequent use of non-core frame elements; more frequent omission of some core frame elements; increased preference for noun phrases rather than clauses as verb arguments; and more frequent metaphoric usage. These characteristics can potentially be useful for automatic prediction of text readability.- Anthology ID:
- 2020.framenet-1.8
- Volume:
- Proceedings of the International FrameNet Workshop 2020: Towards a Global, Multilingual FrameNet
- Month:
- May
- Year:
- 2020
- Address:
- Marseille, France
- Editors:
- Tiago T. Torrent, Collin F. Baker, Oliver Czulo, Kyoko Ohara, Miriam R. L. Petruck
- Venue:
- Framenet
- SIG:
- Publisher:
- European Language Resources Association
- Note:
- Pages:
- 56–62
- Language:
- English
- URL:
- https://aclanthology.org/2020.framenet-1.8
- DOI:
- Cite (ACL):
- John Lee, Meichun Liu, and Tianyuan Cai. 2020. Using Verb Frames for Text Difficulty Assessment. In Proceedings of the International FrameNet Workshop 2020: Towards a Global, Multilingual FrameNet, pages 56–62, Marseille, France. European Language Resources Association.
- Cite (Informal):
- Using Verb Frames for Text Difficulty Assessment (Lee et al., Framenet 2020)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-4/2020.framenet-1.8.pdf