Explainable multi-hop dense question answering using knowledge bases and text

The authors promise an explainable question answering system. The explanation aspect was supposed to be explained in section 5.1.3, which is nowhere to be found.
Moreover, my previous feedback was not addressed.

Regarding the response letter, I think it is not completely aligned with the current version of the article. For example, the authors mention that "In evaluation section we added 'Links are established between words in Wikipedia sentences and DBpedia knowledge base entities using SMART and REL[1]'", however that text and references does not appear in the article. It is also stated that "This operation is called PE for short (See Figure 3)", but that figure does not contain that information, it seems to refer to Figure 5, but in that figure PI is mentioned, not PE. I would appreciate the authors to check the status of the article before writing the response letter.

Regarding the content, the paper now facilitates reproducibility since it publishes the source code of the methods. The description of their proposal has also been improved, mainly the expansion of the graph, and it is in line with the results of the evaluation. In this regard, it is necessary to specify, either in the title or in the abstract, that this method requires not only the natural language question, but also the entities previously identified in the knowledge base. Minor errors have also been corrected.

I really appreciated the authors effort in addressing the reviewers comments. However, now the paper is really verbose and descriptive on technical parts. Many parts are more tailored for a technical paper than for a scientific paper. Another concern is on the contribution of this paper. This has been answered in the answers to my previous questions:

"The theory section discusses the theoretical issues that led to the proposed method for solving the challenges. The first challenge is the inability of hybrid systems to answer questions whose answers do not exist in the knowledge base and must be extracted from the text. To solve this problem, an information retrieval based system was used. The next major challenge is the inability of the existing hybrid systems to explain, which was made possible by the probabilistic method. In addition, query decomposition is not performed in existing hybrid systems. The results showed that by performing this operation, which is based on the function of the human mind, the efficiency of the system increases."

This sentence clearly expresses one of the main paper contributions. I would write it in the paper. In addition, the second finding provides an useful insight on the contribution of this paper, it would be useful to read it summarized at the beginning of the paper. I suggest to make the paper less technical by selecting in Section 5 only the scientific important points and leaving the technicalities in a separate section/appendix. In addition, I would pair Fig. 2 with a running example. Such a running example could be use even in Section 5 to better explain the single modules of the system. In addition, a single running example going along the whole paper would better help the reader than many single examples.

Minors:
- page 3, the sentence "Efforts have been made to" is repeated;
- Section 5, "The motivation for using these 3 axes is given in Section 7.3" I would summarize such a motivation here.
- Section 5, last paragraph, triples and facts are used interchangeably.
- Section 5, last paragraph, the sentence "In addition, ... a single sentence" is not clear.
- Section 5.1, second sentence, correct in "This architecture is shown in Figure3. Figure 4 illustrates ..."