Task: Language Identification
Input (Spanish, English): - Strengths: Nicely written and understandable. Clearly organized. Targeted answering of research questions, based on  different experiments.  - Weaknesses: Minimal novelty. The "first sentence" heuristic has been in the summarization literature for many years. This work essentially applies this heuristic (evolved) in the keyword extraction setting. This is NOT to say that the work is trivial: it is just not really novel.  Lack of state-of-the-art/very recent methods. The experiment on the system evaluation vs state-of-the-art systems simply uses strong baselines. Even though the experiment answers the question "does it perform better than baselines?", I am not confident it illustrates that the system performs better than the current state-of-the-art. This somewhat reduces the value of the paper.  - General Discussion: Overall the paper is good and I propose that it be published and presented.   On the other hand, I would propose that the authors position themselves (and the system performance) with respect to: Martinez‐Romo, Juan, Lourdes Araujo, and Andres Duque Fernandez. "SemGraph: Extracting keyphrases following a novel semantic graph‐based approach." Journal of the Association for Information Science and Technology 67.1 (2016): 71-82. (with which the work holds remarkable resemblance in some points)  Le, Tho Thi Ngoc, Minh Le Nguyen, and Akira Shimazu. "Unsupervised Keyphrase Extraction: Introducing New Kinds of Words to Keyphrases." Australasian Joint Conference on Artificial Intelligence. Springer International Publishing, 2016.
Output (English): en