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].
One example: 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.
Solution is here: es
Explanation: This review is written in spanish. Hence, the label is 'es'.

Now, solve this: This paper proposes a weakly supervised, end-to-end neural network model for solving a challenging natural language understanding task. As an extension of the Neural Programmer, this work aims at overcoming the ambiguities imposed by natural language. By predefining a set of operations, the model is able to learn the interface between the language reasoning and answer composition using backpropagation. On the WikiTableQuestions dataset, it is able to achieve a slightly better performance than the traditional semantic parser methods. Overall, this is a very interesting and promising work as it involves a lot of real-world challenges about natural language understanding. The intuitions and design of the model are very clear, but the complication makes the paper a bit difficult to read, which means the model is also difficult to be reimplemented. I would expect to see more details about model ablation and it would help us figure out the prominent parts of the model design.
Solution:
en