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Designing a Constraint Based Parser for Sanskrit

机译:为梵语设计基于约束的解析器

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Verbal understanding (sdbdabodha) of any utterance requires the knowledge of how words in that utterance are related to each other. Such knowledge is usually available in the form of cognition of grammatical relations. Generative grammars describe how a language codes these relations. Thus the knowledge of what information various grammatical relations convey is available from the generation point of view and not the analysis point of view. In order to develop a parser based on any grammar one should then know precisely the semantic content of the grammatical relations expressed in a language string, the clues for extracting these relations and finally whether these relations are expressed explicitly or implicitly. Based on the design principles that emerge from this knowledge, we model the parser as finding a directed Tree, given a graph with nodes representing the words and edges representing the possible relations between them. Further, we also use the Mimdmsd constraint of dkdnksd (expectancy) to rule out non-solutions and sannidhi (proximity) to prioritize the solutions. We have implemented a parser based on these principles and its performance was found to be satisfactory giving us a confidence to extend its functionality to handle the complex sentences.
机译:任何话语的言语理解(Sdbdabodha)都需要了解这种话语如何彼此相关的单词。这些知识通常以语法关系的认知形式提供。生成语法描述了语言如何代码这些关系。因此,从生成的角度而不是分析的角度来看,可以获得各种语法关系传达的信息的知识。为了开发基于任何语法的解析器,然后应该完全知道语言字符串中表达的语法关系的语义内容,用于提取这些关系的线索,最后是明确或隐含地表达这些关系。基于从本知识中出现的设计原则,我们将解析器模拟为查找定向树,给定具有表示表示它们之间可能关系的单词和边的节点的图表。此外,我们还使用DKDNKSD(寿命)的MIMDMSD约束来排除非解决方案和Sannidhi(接近)以优先考虑解决方案。我们根据这些原则实施了一个解析器,并且发现其性能令人满意使我们能够扩展其功能来处理复杂句子的信心。

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