Ambiguity is a natural language phenomenon occurring at different levels of syntax, semantics, and pragmatics. It is widely studied; in Psycholinguistics, for instance, we have a variety of competing studies for the human disambiguation processes. These studies are empirical and based on eyetracking measurements. Here we take first steps towards formalizing these processes for semantic ambiguities where we identified the presence of two features: (1) joint plausibility degrees of different possible interpretations, (2) causal structures according to which certain words play a more substantial role in the processes. The novel sheaf-theoretic model of definite causality developed by Gogioso and Pinzani in QPL 2021 offers tools to model and reason about these features. We applied this theory to a dataset of ambiguous phrases extracted from Psycholinguistics literature and their human plausibility judgements collected by us using the Amazon Mechanical Turk engine. We measured the causal fractions of different disambiguation orders within the phrases and discovered two prominent orders: from subject to verb in the subject-verb and from object to verb in the verb object phrases. We also found evidence for delay in the disambiguation of polysemous vs homonymous verbs, again compatible with Psycholinguistic findings.

翻译：歧义是一种自然语言现象，发生在句法、语义和语用等不同层面。该现象已被广泛研究：例如在心理语言学中，针对人类消歧过程存在多种相互竞争的研究。这些研究以眼动追踪测量为基础，属于实证范畴。本文针对语义歧义现象，首次尝试从形式化角度刻画该过程，识别出两个关键特征：（1）不同可能解释的联合可信度层级；（2）特定词汇在过程中起更关键作用的因果结构。Gogioso 与 Pinzani 在 QPL 2021 中提出的新型层论因果模型为建模和推理这些特征提供了理论工具。我们将该理论应用于从心理语言学文献中提取的歧义短语数据集，并通过亚马逊机械土耳其人平台收集了人类对短语的可信度判断。通过测量短语中不同消歧顺序的因果分数，我们发现了两种主要模式：主语-动词短语中从主语到动词的消歧顺序，以及动词-宾语短语中从宾语到动词的消歧顺序。研究还发现多义词与同形异义动词在消歧时间滞后上的差异，这与心理语言学的研究发现吻合。