A practical perspective on connective generation

Frances Yung, Merel Scholman, Vera Demberg


Abstract
In data-driven natural language generation, we typically know what relation should be expressed and need to select a connective to lexicalize it. In the current contribution, we analyse whether a sophisticated connective generation module is necessary to select a connective, or whether this can be solved with simple methods (such as random choice between connectives that are known to express a given relation, or usage of a generic language model). Comparing these methods to the distributions of connective choices from a human connective insertion task, we find mixed results: for some relations, it is acceptable to lexicalize them using any of the connectives that mark this relation. However, for other relations (temporals, concessives) either a more detailed relation distinction needs to be introduced, or a more sophisticated connective choice module would be necessary.
Anthology ID:
2021.codi-main.7
Volume:
Proceedings of the 2nd Workshop on Computational Approaches to Discourse
Month:
November
Year:
2021
Address:
Punta Cana, Dominican Republic and Online
Editors:
Chloé Braud, Christian Hardmeier, Junyi Jessy Li, Annie Louis, Michael Strube, Amir Zeldes
Venue:
CODI
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
72–83
Language:
URL:
https://aclanthology.org/2021.codi-main.7
DOI:
10.18653/v1/2021.codi-main.7
Bibkey:
Cite (ACL):
Frances Yung, Merel Scholman, and Vera Demberg. 2021. A practical perspective on connective generation. In Proceedings of the 2nd Workshop on Computational Approaches to Discourse, pages 72–83, Punta Cana, Dominican Republic and Online. Association for Computational Linguistics.
Cite (Informal):
A practical perspective on connective generation (Yung et al., CODI 2021)
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