Deexaggeration

Li Kong and Chuanyi Li and Vincent Ng.
Proceedings of the 31st International Joint Conference on Artificial Intelligence and the 25th European Conference on Artificial Intelligence, pp. 4185-4192, 2022.

Click here for the PDF version.

Abstract

We introduce a new task in hyperbole processing, deexaggeration, which concerns the recovery of the meaning of what is being exaggerated in a hyperbolic sentence in the form of a structured representation. In this paper, we lay the groundwork for the computational study of understanding hyperbole by (1) defining a structured representation to encode what is being exaggerated in a hyperbole in a non-hyperbolic manner, (2) annotating the hyperbolic sentences in two existing datasets, HYPO and HYPO-cn, using this structured representation, (3) conducting an empirical analysis of our annotated corpora, and (4) presenting preliminary results on the deexaggeration task.

BibTeX entry

@InProceedings{Kong+etal:22a,
  author = {Li Kong and Chuanyi Li and Vincent Ng},
  title = {Deexaggeration},
  booktitle = {Proceedings of the 31st International Joint Conference on Artificial Intelligence and the 25th European Conference on Artificial Intelligence},
  pages = {4185--4192}, 
  year = 2022}