Annotating Discursive Roles of Sentences in Patent Descriptions

Lufei Liu (1) , Xu Sun (1, 2) , François Veltz (1) , Kim Gerdes (1, 3)

1 Qatent - Qatent SAS
2 UPCité - Université Paris Cité
3 LISN - Laboratoire Interdisciplinaire des Sciences du Numérique

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.

Mots clés: Discourse Parsing; Patent Analysis; Discourse Parsing

Domaines: Linguistique; Machine Learning [stat.ML]

Lufei Liu, Xu Sun, François Veltz, Kim Gerdes. Annotating Discursive Roles of Sentences in Patent Descriptions. Linguistic Annotation Workshop 2023, ACL, Jul 2023, Toronto, Canada. pp.235-244. ⟨hal-04408308⟩