This dataset was created within the EU-funded project EXCITEMENT as gold standard data to evaluate the task of automatic Textual Entailment Graph (TEG) generation, and is available for English and Italian. A TEG is a directed graph where each node is a complete natural language text (textual fragment) fi and each edge (fi, fj) represents an entailment relation from fi to fj. A textual entailment (fi, fj) holds if the meaning of fi implies the meaning of fj, according to the standard definition of textual entailment which states that fi entails fj if, typically, a human reading fi would infer that fj is most likely true. Given a set of textual fragments (graph nodes), the task of constructing a TEG is to recognize all the entailments among the fragments, i.e. deciding which directional edges connect which pairs of nodes. The main difference between this task and the traditional Recognizing Textual Entailment (RTE) task is that the text pairs are not independent. The nodes in the graph are inter-connected via entailment edges, which should not represent contradicting decisions. For example, if the edges (u,v) and (v,w) are in the graph, then the edge (u,w) is implied by transitivity.