Efficient communication requires balancing informativity and simplicity when encoding meanings. The Information Bottleneck (IB) framework captures this trade-off formally, predicting that natural language systems cluster near an optimal accuracy-complexity frontier. While supported in visual domains such as colour and motion, linguistic stimuli such as words in sentential context remain unexplored. We address this gap by framing translation as an IB optimisation problem, treating source sentences as stimuli and target sentences as compressed meanings. This allows IB analyses to be performed directly on bitexts rather than controlled naming experiments. We applied this to spatial prepositions across English, German and Serbian translations of a French novel. To estimate informativity, we conducted a pile-sorting pilot-study (N=35) and obtained similarity judgements of pairs of prepositions. We trained a low-rank projection model (D=5) that predicts these judgements (Spearman correlation: 0.78). Attested translations of prepositions lie closer to the IB optimal frontier than counterfactual alternatives, offering preliminary evidence that human translators exhibit communicative efficiency pressure in the spatial domain. More broadly, this work suggests that translation can serve as a window into the cognitive efficiency pressures shaping cross-linguistic semantic systems.

翻译：高效交流需要在编码意义时平衡信息性与简洁性。信息瓶颈框架形式化地刻画了这一权衡，预测自然语言系统聚集于最优准确率-复杂度边界附近。虽然该理论在颜色、运动等视觉领域已获验证，但诸如句子语境中的词语等语言刺激仍待探索。我们通过将翻译重构为信息瓶颈优化问题来填补这一空白——将源语句视为刺激，目标语句视为压缩后的意义。这使得信息瓶颈分析可直接应用于双文本而非受控命名实验。我们将其应用于法语小说英、德、塞尔维亚语译本中的空间介词。为评估信息性，我们开展了堆排序预实验（N=35）并获取介词对相似度判断，训练了预测这些判断的低秩投影模型（D=5，斯皮尔曼相关系数：0.78）。实际译文中的介词相较反事实替代项更接近信息瓶颈最优边界，初步证明人类译者在空间域存在交际效率压力。更广泛而言，本研究揭示翻译可成为透视塑造跨语言语义系统的认知效率压力的窗口。