Task: Language Identification
Input (Spanish, English): This paper presents several weakly supervised methods for developing NERs. The methods rely on some form of projection from English into another language. The overall approach is not new and the individual methods proposed are improvements of existing methods. For an ACL paper I would have expected more novel approaches.  One of the contributions of the paper is the data selection scheme. The formula used to calculate the quality score is quite straightforward and this is not a bad thing. However, it is unclear how the thresholds were calculated for Table 2. The paper says only that different thresholds were tried. Was this done on a development set? There is no mention of this in the paper. The evaluation results show clearly that data selection is very important, but one may not know how to tune the parameters for a new data set or a new language pair.   Another contribution of the paper is the combination of the outputs of the two systems developed in the paper. I tried hard to understand how it works, but the description provided is not clear.   The paper presents a number of variants for each of the methods proposed. Does it make sense to combine more than two weakly supervised systems? Did the authors try anything in this direction.  It would be good to know a bit more about the types of texts that are in the "in-house" dataset.
Output (English): en