The specific examples you mentioned seem to contradict the general question you are asking. The sentence fragments, S1 and S2 has some surface-level similarity, but are very different semantically; the object that's beautiful is not the same.
Having said that, to answer your broader question, Semeval 2012 and 2013 focused on Semantic Textual Similarity.
Semantic Textual Similarity (STS) measures the degree of semantic equivalence. We are proposing this STS task as an initial attempt at creating a unified framework that allows for an extrinsic evaluation of multiple semantic components that otherwise have historically tended to be evaluated independently and without characterization of impact on NLP applications. As a pilot task for Semeval 2012, we will focus on refining the task definition as well as producing experimental results on how well existing approaches to semantic equivalence perform. In parallel, we will gather feedback from the community about establishing a shared software framework for building STS annotation systems. The shared STS framework will allow researchers across the globe to more easily replicate and improve upon innovations developed at other sites.
STS is related to both Textual Entailment (TE) and Paraphrase, but differs in a number of ways and it is more directly applicable to a number of NLP tasks. STS is different from TE inasmuch as it assumes bidirectional graded equivalence between the pair of textual snippets. In the case of TE the equivalence is directional, e.g. a car is a vehicle, but a vehicle is not necessarily a car. STS also differs from both TE and Paraphrase in that, rather than being a binary yes/no decision (e.g. a vehicle is not a car), STS is a graded similarity notion (e.g. a vehicle and a car are more similar than a wave and a car). This graded bidirectional nature of STS is useful for NLP tasks such as MT evaluation, information extraction, question answering, and summarization.
You can find the published papers at S12 and S13, the relevant sections of the ACL anthology.