TY - GEN
T1 - Generating Pragmatically Appropriate Sentences from Logic
T2 - The Case of the Conditional and Biconditional
AU - Pei, Renhao
AU - van Deemter, Kees
N1 - Publisher Copyright:
© 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
PY - 2023/3/12
Y1 - 2023/3/12
N2 - It is widely assumed that there exist mismatches between the connectives of Propositional Logic and their counterparts in Natural Language. One mismatch that has been extensively discussed is Conditional Perfection, the phenomenon in which a conditional sentence is interpreted as a biconditional under some circumstances. The Pragmatics literature has provided valuable insights into the question of whether Conditional Perfection will happen in a given context. In order to make these insights more explicit and testable, we designed an algorithm to generate pragmatically more appropriate sentences from propositional logical formulas involving material implication and biconditional implication. This algorithm was tested in an evaluation by human participants, in which generated sentences are compared against those generated by a simple baseline algorithm. The evaluation results suggest that the designed algorithm generates better sentences, which capture the semantics of the logical formulas more faithfully.
AB - It is widely assumed that there exist mismatches between the connectives of Propositional Logic and their counterparts in Natural Language. One mismatch that has been extensively discussed is Conditional Perfection, the phenomenon in which a conditional sentence is interpreted as a biconditional under some circumstances. The Pragmatics literature has provided valuable insights into the question of whether Conditional Perfection will happen in a given context. In order to make these insights more explicit and testable, we designed an algorithm to generate pragmatically more appropriate sentences from propositional logical formulas involving material implication and biconditional implication. This algorithm was tested in an evaluation by human participants, in which generated sentences are compared against those generated by a simple baseline algorithm. The evaluation results suggest that the designed algorithm generates better sentences, which capture the semantics of the logical formulas more faithfully.
KW - Conditional perfection
KW - Propositional logic
KW - Natural language generation
UR - http://www.scopus.com/inward/record.url?scp=85151087665&partnerID=8YFLogxK
U2 - 10.1007/978-3-031-21780-7_8
DO - 10.1007/978-3-031-21780-7_8
M3 - Conference contribution
SN - 9783031217791
T3 - Studies in Computational Intelligence
SP - 171
EP - 190
BT - Logic and Algorithms in Computational Linguistics, LACompLing 2021
A2 - Loukanova, Roussanka
A2 - Lumsdaine, Peter LeFanu
A2 - Muskens, Reinhard
PB - Springer
CY - Cham
ER -