Developments in Sheaf-Theoretic Models of Natural Language Ambiguities

Fuente: arXiv
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Autori principali: Lo, Kin Ian, Sadrzadeh, Mehrnoosh, Mansfield, Shane
Natura: Preprint
Pubblicazione: 2024
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author Lo, Kin Ian
Sadrzadeh, Mehrnoosh
Mansfield, Shane
author_facet Lo, Kin Ian
Sadrzadeh, Mehrnoosh
Mansfield, Shane
contents Sheaves are mathematical objects consisting of a base which constitutes a topological space and the data associated with each open set thereof, e.g. continuous functions defined on the open sets. Sheaves have originally been used in algebraic topology and logic. Recently, they have also modelled events such as physical experiments and natural language disambiguation processes. We extend the latter models from lexical ambiguities to discourse ambiguities arising from anaphora. To begin, we calculated a new measure of contextuality for a dataset of basic anaphoric discourses, resulting in a higher proportion of contextual models-82.9%-compared to previous work which only yielded 3.17% contextual models. Then, we show how an extension of the natural language processing challenge, known as the Winograd Schema, which involves anaphoric ambiguities can be modelled on the Bell-CHSH scenario with a contextual fraction of 0.096.
format Preprint
id arxiv_https___arxiv_org_abs_2402_04505
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Developments in Sheaf-Theoretic Models of Natural Language Ambiguities
Lo, Kin Ian
Sadrzadeh, Mehrnoosh
Mansfield, Shane
Computation and Language
Quantum Physics
Sheaves are mathematical objects consisting of a base which constitutes a topological space and the data associated with each open set thereof, e.g. continuous functions defined on the open sets. Sheaves have originally been used in algebraic topology and logic. Recently, they have also modelled events such as physical experiments and natural language disambiguation processes. We extend the latter models from lexical ambiguities to discourse ambiguities arising from anaphora. To begin, we calculated a new measure of contextuality for a dataset of basic anaphoric discourses, resulting in a higher proportion of contextual models-82.9%-compared to previous work which only yielded 3.17% contextual models. Then, we show how an extension of the natural language processing challenge, known as the Winograd Schema, which involves anaphoric ambiguities can be modelled on the Bell-CHSH scenario with a contextual fraction of 0.096.
title Developments in Sheaf-Theoretic Models of Natural Language Ambiguities
topic Computation and Language
Quantum Physics
url https://arxiv.org/abs/2402.04505