Textual Entailment and anaphora resolution

Textual entailment has been recently defined as a common solution for modeling language variability in different NLP tasks. Textual Entailment is formally defined as a relationship between a coherent text T and a language expression, the hypothesis H. T is said to entail H (T → H) if the meaning of H can be inferred from the meaning of T. An entailment function e(T,H) thus maps an entailment pair T-H to a true value (i.e., true if the relationship holds, false otherwise). Alternatively, e(T,H) can be also intended as a probabilistic function mapping the pair T-H to a real value between 0 and 1, expressing the confidence with which a human judge or an automatic system estimate the relationship to hold.