Reviewer has chosen not to be Anonymous

Overall Impression: Average

Content:
Technical Quality of the paper: Good
Originality of the paper: Yes, but limited
Adequacy of the bibliography: Yes

Presentation:
Adequacy of the abstract: Yes
Introduction: background and motivation: Good
Organization of the paper: Satisfactory
Level of English: Satisfactory
Overall presentation: Good

Detailed Comments:

I have read the revised paper and the detailed replies that the authors included at the end. I’m in favor of accepting the paper as is.

Reviewer has chosen to be Anonymous

Overall Impression: Good

Content:
Technical Quality of the paper: Good
Originality of the paper: Yes
Adequacy of the bibliography: Yes

Presentation:
Adequacy of the abstract: Yes
Introduction: background and motivation: Good
Organization of the paper: Satisfactory
Level of English: Satisfactory
Overall presentation: Excellent

Detailed Comments:

I would like to thank the authors for addressing my comments. Most of my issues were related to presentation and structure and they have all been addressed. I still think this paper is a useful contribution to this special issue.

I still find it a bit weird that Fig. 11. contains both DL and Graph DL (I am aware that in the text the authors have specifically mentioned that they exclude Graph DL from the DL), but I think this could be just a subjective comment and since it is mentioned in the text it should not be a problem.

I also appreciate the addition to the limitation section. Note that probably in replying to my comments and to R1's comments the authors might have said the same thing two times i.e., the "LLMs for knowledge engineering patterns are not in this paper because of data collection." Just pointing this out in case the authors want to streamline the section, there is no real need to address this.

To be honest, I am not sure about the additional value brought by section 5, but I understand this was added as a response to R3. I'd still suggest the authors to improve the quality of Figure 12b (most figures seem to be low quality, but this one is particularly blurry).

Reviewer has chosen to be Anonymous

Overall Impression: Average

Content:
Technical Quality of the paper: Average
Originality of the paper: Yes, but limited
Adequacy of the bibliography: Yes

Presentation:
Adequacy of the abstract: Yes
Introduction: background and motivation: Good
Organization of the paper: Satisfactory
Level of English: Satisfactory
Overall presentation: Good

Detailed Comments:

I think knowledge engineering is a challenging topic, and I understand that the survey tries to cover the key points. However, I'm concerned that there isn't enough information on the symbolic side or the logical side to suggest how people might benefit from this review beyond simply seeing it as a collection of related papers. They have added a new section to tackle my concern about the relevance to semantic web resources. So I suppose the concerns have been addressed, but nonetheless, it would have been more interesting to see a detailed discussion of the technical constructions for knowledge engineering. As it stands, I suppose it's okay.