Using Verb Frames for Text Difficulty Assessment

John Lee, Meichun Liu, Tianyuan Cai


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:
Bibkey:
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)
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PDF:
https://aclanthology.org/2020.framenet-1.8.pdf