AI 中文总结
该研究首次将基于预群语法的量子组合自然语言处理应用于阿拉伯语，通过将句子转换为拓扑反映语法结构的量子电路进行实验，对比量子电路方法与经典基线，为阿拉伯语处理提供新途径。
AI 中文摘要
我们首次将基于预群语法的量子组合自然语言处理（QNLP）应用于阿拉伯语，这是一种形态丰富、词序自由的语言，其结构复杂性为量子电路中的意义组合理论提供了极具挑战性的测试平台。我们的系统将阿拉伯语句子转换为量子电路，其拓扑结构反映语法结构，主语、动词和宾语成为量子门，它们之间的类型依赖关系决定了这些门如何连接。我们进行了三项对照实验，比较量子电路方法与包括AraVec（阿拉伯词嵌入）和AraBERT（预训练阿拉伯语变压器）在内的经典基线。
英文摘要
We present the first application of pregroup grammar-based quantum compositional natural language processing (QNLP) to Arabic; a morphologically rich, free-word-order language whose structural complexity provides a uniquely demanding testbed for theories of meaning composition in quantum circuits. Our system converts Arabic sentences into quantum circuits whose topology mirrors grammatical structure: subjects, verbs, and objects become quantum gates, and the typed dependencies between them (the pregroup grammar) determine how those gates are wired together. We conduct three controlled experiments spanning word order, morphological tense, and verb sense disambiguation, comparing quantum circuit methods against classical baselines including AraVec (Arabic word embeddings) and AraBERT (a pre-trained Arabic transformer).
Comments32 pages, also published here: https://zenodo.org/records/19564468
