In this task, you are given a paper review. Based on the review, your job is to identify language and generate "en" if the review is in English or generate "es" if the review is in Spanish. Note that URLs in the text have been replaced with [Link].

Example input: Este articulo no es un articulo de investigacion, ya que solo muestra como programar un robot mediante la herramienta de logica difusa. Este tema ya ha sido propuesto como solucion en navegacion de robots.
Example output: es
Example explanation: This review is written in spanish. Hence, the label is 'es'.
Q: This paper explores the use of Open Bigrams as a target representation of words, for application to handwriting image recognition. Pros: - The use of OBs is novel and interesting. - Clearly written and explained. Cons: - No comparison to previous state of the art, only with author-generated results. - More ablation studies needed -- i.e. fill in Table3 with rnn0,1 rnn0,1,2 rnn0,1' etc etc. It is not clear where the performance is coming from, as it seems that it is single character modelling (0) and word endings (') that are actually beneficial. - While the use of Open bigrams is novel, there are works which use bag of bigrams and ngrams as models which are not really compared to or explored. E.g.
A:
en