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Tree-to-Graph Transductions with Scope

机译:具有范围的树到图转换

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摘要

High-level natural language processing requires formal languages to represent semantic information. A recent addition of this kind is abstract meaning representations. These are graphs in which nodes encode concepts and edges relations. Node-sharing is common, and cycles occur. We show that the required structures can be generated through the combination of (ⅰ) a regular tree grammar, (ⅱ) a sequence of linear top-down tree transducers, and (ⅲ) a fold operator that merges selected nodes. Delimiting the application of the fold operator to connected subgraphs gains expressive power, while keeping the complexity of the associated membership problem in polynomial time.
机译:高级自然语言处理需要形式语言来表示语义信息。这种最近的增加是抽象含义表示。这些是其中节点编码概念和边关系的图。节点共享是常见的,并且会发生周期。我们展示了可以通过组合(ⅰ)常规树语法,(ⅱ)线性自上而下的树换能器序列和(ⅲ)合并所选节点的折叠算子的组合来生成所需的结构。限制将折叠运算符应用于相连的子图可以提高表达能力,同时在多项式时间内保持关联的隶属度问题的复杂性。

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