Abstract
This article presents the first output of the Dutch FrameNet annotation tool, which facilitates both referential- and frame annotations of language-independent corpora. On the referential level, the tool links in-text mentions to structured data, grounding the text in the real world. On the frame level, those same mentions are annotated with respect to their semantic sense. This way of annotating not only generates a rich linguistic dataset that is grounded in real-world event instances, but also guides the annotators in frame identification, resulting in high inter-annotator-agreement and consistent annotations across documents and at discourse level, exceeding traditional sentence level annotations of frame elements. Moreover, the annotation tool features a dynamic lexical lookup that increases the development of a cross-domain FrameNet lexicon.- Anthology ID:
- 2022.lrec-1.5
- Volume:
- Proceedings of the Thirteenth Language Resources and Evaluation Conference
- Month:
- June
- Year:
- 2022
- Address:
- Marseille, France
- Venue:
- LREC
- SIG:
- Publisher:
- European Language Resources Association
- Note:
- Pages:
- 39–50
- Language:
- URL:
- https://aclanthology.org/2022.lrec-1.5
- DOI:
- Cite (ACL):
- Levi Remijnse, Piek Vossen, Antske Fokkens, and Sam Titarsolej. 2022. Introducing Frege to Fillmore: A FrameNet Dataset that Captures both Sense and Reference. In Proceedings of the Thirteenth Language Resources and Evaluation Conference, pages 39–50, Marseille, France. European Language Resources Association.
- Cite (Informal):
- Introducing Frege to Fillmore: A FrameNet Dataset that Captures both Sense and Reference (Remijnse et al., LREC 2022)
- PDF:
- https://preview.aclanthology.org/remove-xml-comments/2022.lrec-1.5.pdf