A Pāṇinian perspective on structural economy in compounds and its application to universal semantic representation

The principle of lāghava (economy), a fundamental concept in the Pāṇinian grammatical tradition, plays an important role in determining derivational preferences in compound formation. This study investigates its relevance within the framework of Universal Semantic Representation (USR), focusing on the analysis of karmadhāraya and bahuvrīhi compounds. By comparing alternative derivational strategies, it demonstrates that semantically equivalent compound structures may differ significantly in representational complexity. The analysis shows that bahuvrīhi-based representations are more economical because they reduce the number of conceptual units and dependency relations by avoiding intermediate derivational layers. The study further extends this discussion to Natural Language Generation (NLG), illustrating that different USR representations can generate semantically equivalent outputs. However, bahuvrīhi-based representations provide a direct, transparent mapping from semantic structure to surface expression, thereby improving computational efficiency. The findings highlight the continuing relevance of the lāghava principle and a practical guideline for optimising semantic representation in computational linguistics.