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Some steps towards the generation of diachronic WordNets

机译:生成历时性WordNet的一些步骤

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We apply hyperbolic embeddings to trace the dynamics of change of conceptual-semantic relationships in a large diachronic scientific corpus (200 years). Our focus is on emerging scientific fields and the increasingly specialized terminology establishing around them. Reproducing high-quality hierarchical structures such as WordNet on a diachronic scale is a very difficult task. Hyperbolic embeddings can map partial graphs into low dimensional, continuous hierarchical spaces, making more explicit the latent structure of the input. We show that starting from simple lists of word pairs (rather than a list of entities with directional links) it is possible to build diachronic hierarchical semantic spaces which allow us to model a process towards specialization for selected scientific fields.
机译:我们使用双曲线嵌入来追踪大型历时科学语料库(200年)中概念-语义关系的变化动态。我们的重点是新兴的科学领域以及围绕它们建立的越来越专业的术语。在历时尺度上重现高质量的层次结构(如WordNet)是一项非常艰巨的任务。双曲嵌入可以将部分图映射到低维的连续层次空间中,从而使输入的潜在结构更加明确。我们表明,从简单的单词对列表(而不是带有方向链接的实体列表)开始,就可以构建历时性分层语义空间,从而使我们能够为特定科学领域的专业化过程建模。

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