|Review Comment: |
Disclaimer: This review was written together with Sebastian Hellmann.
In this revised version of the paper the authors achieved to address all of the critical aspects that have been outlined in the first review. With regard to the minor issues it can be confirmed that orthographic mistakes as well as the score of the calculation have been corrected. Also, the minor technical issues raised have been checked and resolved as far as possible. Furthermore, it is explained that the authors will include versioning information for the dataset and update to SPARQL 1.1 in the next release.
Referring to the major critical points of the previous review, it can be said that the revised paper has been extended by appropriately addressing the critical points. I.e. the following issues are resolved as follows:
*1) Vocabulary use*
The authors added a paragraph in Section 3 which explains their vocabulary use and justifies the modelling choices. The reasons presented in their discussion are scientifically sound and help the reader to understand not only what has been converted to RDF but also why it has been done in this way.
*2) Addition of translation categories*
The authors acknowledge that direct equivalent statements between senses can be established but consider this a task which requires a more careful analysis which will benefit from a deeper investigation in their future work.
*3) Linkage to BabelNet*
The missing part describing how the links to BabelNet were obtained has been added in Section 4. It also includes a quality evaluation which increases the overall quality of the Apertium RDF datasets.
*4) Quality of indirect translations*
Since the submission of the initial paper the authors conducted further and richer graph-based techniques in order to obtain indirect translations. This research has been separately published and is outlined in Section 5. The results indicate the added value of the RDF Apertium dataset in contrast to the source data which leads to simple querying of the multilingual Apertium RDF data graph.
The revised paper now presents a coherent presentation of the Apertium RDF datasets which succeeds in answering the posed questions. Further, it needs to be stressed, that this dataset proves to be up to date, constantly maintained and object of future investigations, which are desirable criteria that hold for dataset publications in general. Finally, the third party use in machine translation is now realized by collaborating with the original Apertium initiative, but also other parties are mentioned that reuse the data, which emphasizes the quality and added value of the Apertium RDF datasets within the Semantic Web and especially the linguistic linked data landscape.