Synonymy appears to violate the principle of least effort, as there is no clear justification for maintaining multiple words with the same meaning. However, according to the principle of no synonymy, any difference in form should entail a difference in meaning.

This study applies information-theoretic measures to quantify contextual differences between near-synonyms. Jensen–Shannon divergence (JSD) is used to measure distributional overlap between synonym pairs, while information gain (IG) captures how specific each word's contextual distribution is. The analysis examines 134 synonym pairs in Hindi, comparing lexemes of Sanskrit origin with their Perso-Arabic counterparts across two corpora (768M and 350M tokens) and four window sizes.

Results show that synonym pairs share substantial contextual overlap (lower JSD than random pairs), yet are not fully interchangeable (JSD consistently above zero). Analysis of information gain revealed a striking asymmetry: in over 80% of pairs, the Perso-Arabic variant exhibited higher IG than its Sanskrit counterpart. This suggests that Perso-Arabic vocabulary tends to occur in more specific, contextually constrained environments, while Sanskrit variants serve as a more neutral, broadly distributed baseline.

These findings suggest that synonymy, rather than violating the principle of least effort, is a consequence of system optimization. Etymology appears to constrain lexical behavior, leaving lasting semantic footprints long after borrowing. This may point to the existence of loose semantic frames composed of etymologically related words forming coherent conceptual groupings. Further research across languages with layered lexical histories is needed to confirm these patterns.