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].

[Q]: The paper describes an idea to learn phrasal representation and facilitate them in RNN-based language models and neural machine translation  -Strengths:  The  idea to incorporate phrasal information into the task is interesting.  - Weaknesses:  - The description is hard to follow. Proof-reading by an English native speaker would benefit the understanding - The evaluation of the approach has several weaknesses  - General discussion  - In Equation 1 and 2 the authors mention a phrase representation give a fix-length word embedding vector. But this is not used in the model. The representation is generated based on an RNN. What the propose of this description? - Why are you using GRU for the Pyramid and LSTM for the sequential part? Is the combination of two architectures a reason for your improvements? - What is the simplified version of the GRU? Why is it performing better? How is it performing on the large data set? - What is the difference between RNNsearch (groundhog) and RNNsearch(baseline) in Table 4? -  What is the motivation for only using the ending phrases and e.g. not using the starting phrases? - Did you use only the pyramid encoder? How is it performing? That would be a more fair comparison since it normally helps to make the model more complex. - Why did you run RNNsearch several times, but PBNMT only once?  - Section 5.2: What is the intent of this section
[A]: en


[Q]: -	El tema es de relevancia científica. -	En el trabajo se desarrolló un análisis de la literatura sobre calidad de datos en las aplicaciones de e-government municipal. -	Metodológicamente existen tres limitaciones importantes a superar. Primero, no se ha considerado el factor de impacto de la publicaciones, con lo cual se ha desestimado el desarrollo asociado a este tipo de revisiones, mezclando trabajos de alto impacto (ejemplo, artículos de revistas ISIs factor de impacto >2, como MISQ) con trabajos sin una revisión de calidad (ejemplo, lo que Scholar "lanza" sólo por coincidir en la búsqueda). Segundo, se dice que se tomarán referencias del 2008 en adelante prioritariamente, pero muchas de sus referencias  son de antes de esa fecha, y eso no es raro, pues entre 2001 y 2004 hay una explosión de trabajos en este ámbito específico. Tercero, no se han incluido explícitamente trabajos de conferencias del área de alto impacto en la comunidad científica como AMCIS o ECIS (la primera tiene una base de datos privada, no accesible por google y la segunda es libre). -	Las limitaciones antes expuestas restringen los alcances de los interesantes  resultados expuestos en el trabajo. -	Finalmente, se sugiere avanzar en las escalas de medida de dimensiones seleccionadas  antes de desarrollar caso de estudio indicado en las conclusiones.
[A]: es


[Q]: This is an interesting article, present develop of a mobile robot use as beach cleaner.  I have 2 comments about the design, I think will be interesting define what is the dimension of collector and storage compartment for know what is the capacity of this cleaner.  In page 2 in the first paragraph a typo mistake was found.
[A]:
en