Prepositions Matter in Quantifier Scope Disambiguation

Aleksander Leczkowski, Justyna Grudzińska, Manuel Vargas Guzmán, Aleksander Wawer, Aleksandra Siemieniuk


Abstract
Although it is widely agreed that world knowledge plays a significant role in quantifier scope disambiguation (QSD), there has been only very limited work on how to integrate this knowledge into a QSD model. This paper contributes to this scarce line of research by incorporating into a machine learning model our knowledge about relations, as conveyed by a manageable closed class of function words: prepositions. For data, we use a scope-disambiguated corpus created by AnderBois, Brasoveanu and Henderson, which is additionally annotated with prepositional senses using Schneider et al’s Semantic Network of Adposition and Case Supersenses (SNACS) scheme. By applying Manshadi and Allen’s method to the corpus, we were able to inspect the information gain provided by prepositions for the QSD task. Statistical analysis of the performance of the classifiers, trained in scenarios with and without preposition information, supports the claim that prepositional senses have a strong positive impact on the learnability of automatic QSD systems.
Anthology ID:
2022.coling-1.348
Volume:
Proceedings of the 29th International Conference on Computational Linguistics
Month:
October
Year:
2022
Address:
Gyeongju, Republic of Korea
Venue:
COLING
SIG:
Publisher:
International Committee on Computational Linguistics
Note:
Pages:
3960–3970
Language:
URL:
https://aclanthology.org/2022.coling-1.348
DOI:
Bibkey:
Cite (ACL):
Aleksander Leczkowski, Justyna Grudzińska, Manuel Vargas Guzmán, Aleksander Wawer, and Aleksandra Siemieniuk. 2022. Prepositions Matter in Quantifier Scope Disambiguation. In Proceedings of the 29th International Conference on Computational Linguistics, pages 3960–3970, Gyeongju, Republic of Korea. International Committee on Computational Linguistics.
Cite (Informal):
Prepositions Matter in Quantifier Scope Disambiguation (Leczkowski et al., COLING 2022)
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PDF:
https://aclanthology.org/2022.coling-1.348.pdf
Code
 aleczkowski/prep_matter_in_qsd