Abstract
This paper proposes a new task of detecting information override. Since all information on the Web is not updated in a timely manner, the necessity is created for information that is overridden by another information source to be discarded. The task is formalized as a binary classification problem to determine whether a reference sentence has overridden a target sentence. In investigating this task, this paper describes a construction procedure for the dataset of overridden information by collecting sentence pairs from the difference between two versions of Wikipedia. Our developing dataset shows that the old version of Wikipedia contains much overridden information and that the detection of information override is necessary.- Anthology ID:
- 2022.lrec-1.601
- Volume:
- Proceedings of the Thirteenth Language Resources and Evaluation Conference
- Month:
- June
- Year:
- 2022
- 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, Jan Odijk, Stelios Piperidis
- Venue:
- LREC
- SIG:
- Publisher:
- European Language Resources Association
- Note:
- Pages:
- 5601–5608
- Language:
- URL:
- https://aclanthology.org/2022.lrec-1.601
- DOI:
- Cite (ACL):
- Masatoshi Tsuchiya and Yasutaka Yokoi. 2022. Developing a Dataset of Overridden Information in Wikipedia. In Proceedings of the Thirteenth Language Resources and Evaluation Conference, pages 5601–5608, Marseille, France. European Language Resources Association.
- Cite (Informal):
- Developing a Dataset of Overridden Information in Wikipedia (Tsuchiya & Yokoi, LREC 2022)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-1/2022.lrec-1.601.pdf