Resumen: In this work we show that global topological properties of co-occurrent word networks constructed from texts, seem to be the fingerprint of meaningful sentences. We observe that many statistical properties of these networks depend on the frequency of words, however, others seem to be strictly determined by the grammar. Our results suggest that seems to be a lower bound of sense that depends on the correlation between mean word connectivity and word connectivity correlation. This property, in addition to being only present in meaningful texts, and absent in, until now, not decoded texts such as the Voynich manuscript, would also be exclusive for natural languages, allowing us to discriminate between these and formal texts.