Abstract
The present data formats proposed by authentic organizations are based on a so-called standoff-style data format in XML, which represents a semantic data model through an instance structure and a link structure. However, this type of data formats intended to enhance the power of representation of an XML format injures the mobility of data because an abstract data structure denoted by multiple link paths is hard to be converted into other data structures. This difficulty causes a problem in the reuse of data to convert into other data formats especially in a personal data management environment. In this paper, in order to compensate for the drawback, we propose a new concept of transforming a link structure to an instance structure on a new marked-up scheme. This approach to language data brings a new architecture of language data management to realize a personal data management environment in daily and long-life use.- Anthology ID:
- 2022.lrec-1.307
- 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:
- 2865–2873
- Language:
- URL:
- https://aclanthology.org/2022.lrec-1.307
- DOI:
- Cite (ACL):
- Kazushi Ohya. 2022. An Architecture of resolving a multiple link path in a standoff-style data format to enhance the mobility of language resources. In Proceedings of the Thirteenth Language Resources and Evaluation Conference, pages 2865–2873, Marseille, France. European Language Resources Association.
- Cite (Informal):
- An Architecture of resolving a multiple link path in a standoff-style data format to enhance the mobility of language resources (Ohya, LREC 2022)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-4/2022.lrec-1.307.pdf