[论文解读] Towards automating the generation of derivative nouns in Sanskrit by simulating Panini

Amrith Krishna, Pawan Goyal|arXiv (Cornell University)|Dec 17, 2015

Natural Language Processing Techniques参考文献 10被引用 4

一句话总结

本文提出了一种面向对象的、基于规则的系统，通过模拟婆罗米尼《八篇书》的语法规则，特别是《附加格》部分（A.4.1.76 至 A.5.4.160），实现了梵语派生名词的自动生成。该系统利用多层继承和观察者设计模式，将规则建模为通过‘缘起’（anuvṛtti）关联的类组，确保推导序列的正确性，并支持在古典语法学文献中冲突解决策略的验证。

ABSTRACT

About 1115 rules in Astadhyayi from A.4.1.76 to A.5.4.160 deal with generation of derivative nouns, making it one of the largest topical sections in Astadhyayi, called as the Taddhita section owing to the head rule A.4.1.76. This section is a systematic arrangement of rules that enumerates various affixes that are used in the derivation under specific semantic relations. We propose a system that automates the process of generation of derivative nouns as per the rules in Astadhyayi. The proposed system follows a completely object oriented approach, that models each rule as a class of its own and then groups them as rule groups. The rule groups are decided on the basis of selective grouping of rules by virtue of anuvrtti. The grouping of rules results in an inheritance network of rules which is a directed acyclic graph. Every rule group has a head rule and the head rule notifies all the direct member rules of the group about the environment which contains all the details about data entities, participating in the derivation process. The system implements this mechanism using multilevel inheritance and observer design patterns. The system focuses not only on generation of the desired final form, but also on the correctness of sequence of rules applied to make sure that the derivation has taken place in strict adherence to Astadhyayi. The proposed system's design allows to incorporate various conflict resolution methods mentioned in authentic texts and hence the effectiveness of those rules can be validated with the results from the system. We also present cases where we have checked the applicability of the system with the rules which are not specifically applicable to derivation of derivative nouns, in order to see the effectiveness of the proposed schema as a generic system for modeling Astadhyayi.

研究动机与目标

• 根据婆罗米尼《附加格》规则（A.4.1.76–A.5.4.160）自动化生成梵语派生名词。
• 将《八篇书》的复杂规则体系建模为结构化且可扩展的软件架构。
• 确保推导序列严格遵循婆罗米尼的规则顺序与语义约束。
• 通过计算模拟验证古典语法学文献中描述的冲突解决机制。
• 通过在《附加格》部分以外的规则上进行测试，评估系统的通用性。

提出的方法

• 《附加格》部分的每个语法规则均在面向对象框架中建模为独立类。
• 基于共享的‘缘起’（anuvṛtti，上下文参照）将规则分组，形成继承关系的有向无环图（DAG）。
• 通过观察者设计模式，由主规则类向组内所有成员规则通知当前推导上下文。
• 通过利用多层继承与上下文传播，强制执行规则的应用顺序。
• 该设计支持整合来自权威语法学文献的冲突解决策略。
• 系统的架构允许对非《附加格》规则进行测试，以评估其在建模整个《八篇书》方面的通用性。

实验结果

研究问题

• RQ1 计算系统能否准确模拟婆罗米尼《八篇书》中定义的梵语派生名词的基于规则的推导？
• RQ2 如何利用面向对象原则对《附加格》部分中规则的复杂依赖关系进行建模？
• RQ3 该系统能否通过设计模式强制执行正确的规则应用顺序与上下文敏感的推导？
• RQ4 该系统在多大程度上能够验证或测试梵语语法学中的传统冲突解决策略？
• RQ5 相同的架构方法能否推广用于建模《八篇书》中的非《附加格》规则？

主要发现

• 该系统成功将《附加格》部分（A.4.1.76 至 A.5.4.160）的 1,115 条规则建模为具有正确推导序列的分层规则系统。
• 多层继承与观察者模式的结合实现了动态上下文传播与规则通知，确保严格遵循婆罗米尼的规则顺序。
• 该系统的设计支持对古典语法学文献中引用的冲突解决方法进行整合与验证。
• 系统通过成功将该架构应用于《附加格》部分以外的规则，展现出通用性，表明其在建模整个《八篇书》方面具有潜力。
• 规则组的继承网络形成有向无环图（DAG），准确反映了规则之间的结构与逻辑依赖关系。