LinPP: a Python-friendly algorithm for Linear Pregroup Parsing

Irene Rizzo


Abstract
We define a linear pregroup parser, by applying some key modifications to the minimal parser defined in (Preller, 2007). These include handling words as separate blocks, and thus respecting their syntactic role in the sentence. We prove correctness of our algorithm with respect to parsing sentences in a subclass of pregroup grammars. The algorithm was specifically designed for a seamless implementation in Python. This facilitates its integration within the DisCopy module for QNLP and vastly increases the applicability of pregroup grammars to parsing real-world text data.
Anthology ID:
2021.semspace-1.2
Volume:
Proceedings of the 2021 Workshop on Semantic Spaces at the Intersection of NLP, Physics, and Cognitive Science (SemSpace)
Month:
June
Year:
2021
Address:
Groningen, The Netherlands
Editors:
Martha Lewis, Mehrnoosh Sadrzadeh
Venue:
SemSpace
SIG:
SIGSEM
Publisher:
Association for Computational Linguistics
Note:
Pages:
12–19
Language:
URL:
https://aclanthology.org/2021.semspace-1.2
DOI:
Bibkey:
Cite (ACL):
Irene Rizzo. 2021. LinPP: a Python-friendly algorithm for Linear Pregroup Parsing. In Proceedings of the 2021 Workshop on Semantic Spaces at the Intersection of NLP, Physics, and Cognitive Science (SemSpace), pages 12–19, Groningen, The Netherlands. Association for Computational Linguistics.
Cite (Informal):
LinPP: a Python-friendly algorithm for Linear Pregroup Parsing (Rizzo, SemSpace 2021)
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PDF:
https://aclanthology.org/2021.semspace-1.2.pdf