In this paper, we present a set of linguistic rules, employed to enhance the readability of legal texts. The rules were compiled and implemented as a rule-based module of PONK, an advisory tool that contributes to simplification and higher clarity of Czech legal texts, especially those intended for non-expert audience. Based on recurring phenomena in authentic texts and relevant scientific sources, the rules cover mainly the domains of syntax and lexicon. In addition, we present the results of application of the rules to a corpus of authentic legal texts, evaluated by a human annotator, and examine their impact.

We propose a range of automated metrics for evaluation of generated poetry.The metrics measure various aspects of poetry: rhyming, metre, syntax, semantics, and amount of unknown words.In a case study, we implement the metrics for Czech language, apply them to poetry generated by several automated systems as well as human-written, and correlate them with human judgment.We find that most of the proposed metrics correlate well with corresponding human evaluation, but semantically oriented metrics are much better predictors of the overall impression than metrics evaluating formal properties.