TY - GEN
T1 - Polynomial Event Semantics
T2 - 12th International Symposium on Artificial Intelligence supported by the Japanese Society for Artificial Intelligence, JSAI-isAI 2020, International Workshop on Logic and Engineering of Natural Language Semantics, LENLS 2020, 14th International Workshop on Juris-informatics, JURISIN 2020
AU - Kiselyov, Oleg
N1 - Funding Information:
Acknowledgments. I am grateful to anonymous reviewers for very helpful comments and suggestions. I thank Daisuke Bekki for insightful and stimulating questions. This work was partially supported by a JSPS KAKENHI Grant Number 17K00091.
Publisher Copyright:
© 2021, Springer Nature Switzerland AG.
PY - 2021
Y1 - 2021
N2 - Polynomial event semantics is an interpretation of Neo-Davidsonian semantics in which the thorny event quantification problem does not even arise. Denotations are constructed strictly compositionally, from lexical entries up, and quantifiers are analyzed in situ. All advantages of event semantics, in particular, regarding entailment, are preserved. The previous work has dealt only with positive polarity phrases involving universal, existential and counting quantification. We now extend the polynomial event semantics to sentences with negation and negative quantification, including adverbial quantification, with attendant ambiguities. The analysis remains compositional, and does not require positing of non-existing entities or events.
AB - Polynomial event semantics is an interpretation of Neo-Davidsonian semantics in which the thorny event quantification problem does not even arise. Denotations are constructed strictly compositionally, from lexical entries up, and quantifiers are analyzed in situ. All advantages of event semantics, in particular, regarding entailment, are preserved. The previous work has dealt only with positive polarity phrases involving universal, existential and counting quantification. We now extend the polynomial event semantics to sentences with negation and negative quantification, including adverbial quantification, with attendant ambiguities. The analysis remains compositional, and does not require positing of non-existing entities or events.
UR - http://www.scopus.com/inward/record.url?scp=85112228622&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85112228622&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-79942-7_6
DO - 10.1007/978-3-030-79942-7_6
M3 - Conference contribution
AN - SCOPUS:85112228622
SN - 9783030799410
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 82
EP - 95
BT - New Frontiers in Artificial Intelligence - JSAI-isAI 2020 Workshops, JURISIN, LENLS 2020 Workshops, 2020, Revised Selected Papers
A2 - Okazaki, Naoaki
A2 - Yada, Katsutoshi
A2 - Satoh, Ken
A2 - Mineshima, Koji
PB - Springer Science and Business Media Deutschland GmbH
Y2 - 15 November 2020 through 17 November 2020
ER -