Abstract
This submission reports on a three-part series of original methods geared towards producing semantic annotations for the decompositional marker “again”. The three methods are (i) exhaustive expert annotation based on a comprehensive set of guidelines, (ii) extension of expert annotation by predicting presuppositions with a Multinomial Naïve Bayes classifier in the context of a meta-analysis to optimize feature selection and (iii) quality-controlled crowdsourcing with ensuing evaluation and KMeans clustering of annotation vectors.- Anthology ID:
- 2023.law-1.13
- 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:
- 129–135
- Language:
- URL:
- https://aclanthology.org/2023.law-1.13
- DOI:
- 10.18653/v1/2023.law-1.13
- Cite (ACL):
- Martin Kopf and Remus Gergel. 2023. Annotating Decomposition in Time: Three Approaches for Again. In Proceedings of the 17th Linguistic Annotation Workshop (LAW-XVII), pages 129–135, Toronto, Canada. Association for Computational Linguistics.
- Cite (Informal):
- Annotating Decomposition in Time: Three Approaches for Again (Kopf & Gergel, LAW 2023)
- PDF:
- https://preview.aclanthology.org/emnlp-22-attachments/2023.law-1.13.pdf