CNL-ER: A Controlled Natural Language for Specifying and Verbalising Entity Relationship Models

Bayzid Ashik Hossain, Gayathri Rajan, Rolf Schwitter


Abstract
The first step towards designing an information system is conceptual modelling where domain experts and knowledge engineers identify the necessary information together to build an information system. Entity relationship modelling is one of the most popular conceptual modelling techniques that represents an information system in terms of entities, attributes and relationships. Entity relationship models are constructed graphically but are often difficult to understand by domain experts. To overcome this problem, we suggest to verbalise these models in a controlled natural language. In this paper, we present CNL-ER, a controlled natural language for specifying and verbalising entity relationship (ER) models that not only solves the verbalisation problem for these models but also provides the benefits of automatic verification and validation, and semantic round-tripping which makes the communication process transparent between the domain experts and the knowledge engineers.
Anthology ID:
U19-1017
Volume:
Proceedings of the 17th Annual Workshop of the Australasian Language Technology Association
Month:
4--6 December
Year:
2019
Address:
Sydney, Australia
Editors:
Meladel Mistica, Massimo Piccardi, Andrew MacKinlay
Venue:
ALTA
SIG:
Publisher:
Australasian Language Technology Association
Note:
Pages:
126–135
Language:
URL:
https://aclanthology.org/U19-1017
DOI:
Bibkey:
Cite (ACL):
Bayzid Ashik Hossain, Gayathri Rajan, and Rolf Schwitter. 2019. CNL-ER: A Controlled Natural Language for Specifying and Verbalising Entity Relationship Models. In Proceedings of the 17th Annual Workshop of the Australasian Language Technology Association, pages 126–135, Sydney, Australia. Australasian Language Technology Association.
Cite (Informal):
CNL-ER: A Controlled Natural Language for Specifying and Verbalising Entity Relationship Models (Hossain et al., ALTA 2019)
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PDF:
https://aclanthology.org/U19-1017.pdf