用量子电路模拟阿拉伯语语法结构，实现自然语言处理新方法
Quantum Compositional NLP for Arabic: Grammar, Morphology, and Word Sense in Circuit Topology
- 将阿拉伯语句法转为量子门拓扑结构，依预组语法连接
- 在词序、时态、动词歧义消解上优于经典模型
- 适合对量子自然语言处理与阿拉伯语技术感兴趣的读者
我们首次将基于预组语法的量子组合自然语言处理（QNLP）应用于阿拉伯语——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独特挑战。系统将阿拉伯语句子转换为量子电路，其中主语、谓语、宾语转化为量子门，而类型化依赖关系（预组语法）决定这些门的连接方式。我们设计了三项受控实验，涵盖词序、形态时态和动词语义消歧，对比了量子电路方法与经典基线模型AraVec（阿拉伯语词向量）和AraBERT（预训练阿拉伯语Transformer）的表现。
原文摘要 · Abstract (English)
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).
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。