ResPubliQA is a Question Answering (QA) evaluation task over European legislation whose first edition
was proposed at the Cross Language Evaluation Forum (CLEF) 2009. The exercise consists of extracting
a relevant paragraph of text that satisfies the information need expressed by a natural language question.
The definition of the task allows to compare current QA technologies with pure Information Retrieval (IR)
approaches and to introduce Answer Validation technologies in QA systems. In this paper we describe a
system developed for this task. Our system is composed by an IR phase focused on improving QA results,
a validation step for removing not promising paragraphs and a module based on n-grams overlapping for
selecting the final answer, as well as a selection module that uses Lexical Entailment. While the IR module
has contributed to obtain promising results, the performance of the validation module has to be
improved. On the other hand, the n-gram ranking improved the results of the ranking given by the IR
module.