Annotating Discursive Roles of Sentences in Patent Descriptions

Lufei Liu, Xu Sun, François Veltz, Kim Gerdes


Abstract
Patent descriptions are a crucial component of patent applications, as they are key to understanding the invention and play a significant role in securing patent grants. While discursive analyses have been undertaken for scientific articles, they have not been as thoroughly explored for patent descriptions, despite the increasing importance of Intellectual Property and the constant rise of the number of patent applications. In this study, we propose an annotation scheme containing 16 classes that allows categorizing each sentence in patent descriptions according to their discursive roles. We publish an experimental human-annotated corpus of 16 patent descriptions and analyze challenges that may be encountered in such work. This work can be base for an automated annotation and thus contribute to enriching linguistic resources in the patent domain.
Anthology ID:
2023.law-1.23
Volume:
Proceedings of the 17th Linguistic Annotation Workshop (LAW-XVII)
Month:
July
Year:
2023
Address:
Toronto, Canada
Editors:
Jakob Prange, Annemarie Friedrich
Venue:
LAW
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
235–243
Language:
URL:
https://aclanthology.org/2023.law-1.23
DOI:
10.18653/v1/2023.law-1.23
Bibkey:
Cite (ACL):
Lufei Liu, Xu Sun, François Veltz, and Kim Gerdes. 2023. Annotating Discursive Roles of Sentences in Patent Descriptions. In Proceedings of the 17th Linguistic Annotation Workshop (LAW-XVII), pages 235–243, Toronto, Canada. Association for Computational Linguistics.
Cite (Informal):
Annotating Discursive Roles of Sentences in Patent Descriptions (Liu et al., LAW 2023)
Copy Citation:
PDF:
https://aclanthology.org/2023.law-1.23.pdf