Task: Language Identification
Input (Spanish, English): - General Discussion:  This paper extends Zhou and Xu's ACL 2015 approach to semantic role labeling based on deep BiLSTMs. In addition to applying recent best practice techniques, leading to further quantitative improvements, the authors provide an insightful qualitative analysis of their results. The paper is well written and has a clear structure. The authors provide a comprehensive overview of related work and compare results to a representative set of other SRL models that hace been applied on the same data sets.  I found the paper to be interesting and convincing. It is a welcome research contribution that not only shows that NNs work well, but also analyzes merits and shortcomings of an end-to-end learning approach.  - Strengths:  Strong model, insightful discussion/error analysis.  - Weaknesses:  Little to no insights regarding the SRL task itself.
Output (English): en