Thirty Musts for Meaning Banking

Lasha Abzianidze, Johan Bos


Abstract
Meaning banking—creating a semantically annotated corpus for the purpose of semantic parsing or generation—is a challenging task. It is quite simple to come up with a complex meaning representation, but it is hard to design a simple meaning representation that captures many nuances of meaning. This paper lists some lessons learned in nearly ten years of meaning annotation during the development of the Groningen Meaning Bank (Bos et al., 2017) and the Parallel Meaning Bank (Abzianidze et al., 2017). The paper’s format is rather unconventional: there is no explicit related work, no methodology section, no results, and no discussion (and the current snippet is not an abstract but actually an introductory preface). Instead, its structure is inspired by work of Traum (2000) and Bender (2013). The list starts with a brief overview of the existing meaning banks (Section 1) and the rest of the items are roughly divided into three groups: corpus collection (Section 2 and 3, annotation methods (Section 4–11), and design of meaning representations (Section 12–30). We hope this overview will give inspiration and guidance in creating improved meaning banks in the future
Anthology ID:
W19-3302
Volume:
Proceedings of the First International Workshop on Designing Meaning Representations
Month:
August
Year:
2019
Address:
Florence, Italy
Venues:
ACL | DMR | WS
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
15–27
Language:
URL:
https://aclanthology.org/W19-3302
DOI:
10.18653/v1/W19-3302
Bibkey:
Cite (ACL):
Lasha Abzianidze and Johan Bos. 2019. Thirty Musts for Meaning Banking. In Proceedings of the First International Workshop on Designing Meaning Representations, pages 15–27, Florence, Italy. Association for Computational Linguistics.
Cite (Informal):
Thirty Musts for Meaning Banking (Abzianidze & Bos, 2019)
Copy Citation:
PDF:
https://preview.aclanthology.org/update-css-js/W19-3302.pdf
Data
AMR BankFrameNetGroningen Meaning Bank