metaphactory: A Platform for Knowledge Graph Management

This revision has implemented all the suggestions I provided in the last round. I recommend that the paper can be accepted now.

The quality of the paper is very good, The suggested tool is important and covers the limitations of most others knowledge management platforms, and the metaphactory platform is a powerful and successful knowledge management platform.
The suggested tool has a great impact on organizations due to offer capabilities and features to support the entire life cycle of dealing with knowledge graphs and is used in production in a variety of use cases involving knowledge graph management in different application domains.

This manuscript was submitted as 'Tools and Systems Report' and should be reviewed along the following dimensions:
(1) Quality, importance, and impact of the described tool or system (convincing evidence must be provided). (2) Clarity, illustration, and readability of the describing paper, which shall convey to the reader both the capabilities and the limitations of the tool.

(1) Quality, importance, and impact of the described tool or system (convincing evidence must be provided).

Knowledge graph is gaining a lot of attention these days especially with the data explosion. For people working in the field,
the creating and maintaining a knowledge graph is definitely a nightmare even with all the advances in the field of semantic web. So I think
this topic is very relevant, but I think the tool is too ambitious to capture all the three applications of a knowledge graph: 1) Data population, 2) End-user interaction, 3) Application-development.

(2) Clarity, illustration, and readability of the describing paper

I feel the introduction could have motivated better, may be you should have started with challenges using an existing system that can do one or more of the applications of a knowledge graph.
I wonder the size of the graphs you used for case studies, I checked few of them, it was less than 100M nodes. I wonder what if the graph is not small enough for a single machine and also how will the application API scale if they are all talking to the same graph.

(3) Usability

I was expecting the authors to conduct: 1) Usability, 2) Performance (execution time) , and 3) Development time evaluations of the metaphactory implementations with that of the other implementations.
In the paper, authors show that metaphactory can also realize these usecases, but that is not motivation for existing applications to move to metaphactory or new organizations to use metaphactory unless they are convinced of the key advantages and compromises.
Readers also like to review the related tools in the domain and contrast the key advantages of using metaphactory.