Graph-based semantic representations are valuable in natural language processing, where it is often simple and effective to represent linguistic concepts as nodes, and relations as edges between them. Several attempts has been made to find a generative device that is sufficiently powerful to represent languages of semantic graphs, while at the same allowing efficient parsing. We add to this line of work by introducing graph extension grammar, which consists of an algebra over graphs together with a regular tree grammar that generates expressions over the operations of the algebra. Due to the design of the operations, these grammars can generate graphs with non-structural reentrancies; a type of node-sharing that is excessively common in formalisms such as abstract meaning representation, but for which existing devices offer little support. We provide a parsing algorithm for graph extension grammars, which is proved to be correct and run in polynomial time.
翻译:基于图形的语义表达方式在自然语言处理中很有价值,在自然语言处理中,将语言概念作为节点和关系作为节点来代表往往简单而有效。已经多次尝试寻找一种能够代表语义图语言的基因化装置,同时允许有效解析。我们通过引入图形扩展语法来增加这一工作线,该语法由图形的代数和普通树形语法组成,在代数操作中产生表达方式。由于操作的设计,这些语法可以产生非结构性重置的图表;一种在形式主义中过于常见的节点共享方式,如抽象含义表达方式,但现有的设备对此几乎没有支持。我们为图形扩展语法提供了一种解算法,这种算法被证明是正确和在多边时间运行的。