Representing Implicit Positive Meaning of Negated Statements in AMR

Katharina Stein, Lucia Donatelli


Abstract
Abstract Meaning Representation (AMR) has become popular for representing the meaning of natural language in graph structures. However, AMR does not represent scope information, posing a problem for its overall expressivity and specifically for drawing inferences from negated statements. This is the case with so-called “positive interpretations” of negated statements, in which implicit positive meaning is identified by inferring the opposite of the negation’s focus. In this work, we investigate how potential positive interpretations (PPIs) can be represented in AMR. We propose a logically motivated AMR structure for PPIs that makes the focus of negation explicit and sketch an initial proposal for a systematic methodology to generate this more expressive structure.
Anthology ID:
2021.law-1.3
Volume:
Proceedings of the Joint 15th Linguistic Annotation Workshop (LAW) and 3rd Designing Meaning Representations (DMR) Workshop
Month:
November
Year:
2021
Address:
Punta Cana, Dominican Republic
Editors:
Claire Bonial, Nianwen Xue
Venue:
LAW
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
23–35
Language:
URL:
https://aclanthology.org/2021.law-1.3
DOI:
10.18653/v1/2021.law-1.3
Bibkey:
Cite (ACL):
Katharina Stein and Lucia Donatelli. 2021. Representing Implicit Positive Meaning of Negated Statements in AMR. In Proceedings of the Joint 15th Linguistic Annotation Workshop (LAW) and 3rd Designing Meaning Representations (DMR) Workshop, pages 23–35, Punta Cana, Dominican Republic. Association for Computational Linguistics.
Cite (Informal):
Representing Implicit Positive Meaning of Negated Statements in AMR (Stein & Donatelli, LAW 2021)
Copy Citation:
PDF:
https://aclanthology.org/2021.law-1.3.pdf