Peer Review History

Original SubmissionOctober 14, 2023
Decision Letter - John Blake, Editor

PONE-D-23-33628Creating and Validating the Fine-Grained Question Subjectivity Dataset (FSQD): a new benchmark for enhanced Automatic Subjective Question Answering systemsPLOS ONE

Dear Dr. Fatemi,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

We appreciate the effort and expertise you have brought to your work; however, several areas have been identified that need significant improvement. Please find the detailed and actionable comments below. The comments from point three onwards are of particular importance. These suggestions are aimed at enhancing the clarity, depth, and overall quality of your manuscript. I concur with the reviewer comments and believe that addressing these points will substantially strengthen your paper. 

Please submit your revised manuscript by Feb 25 2024 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

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We look forward to receiving your revised manuscript.

Kind regards,

John Blake, PhD

Academic Editor

PLOS ONE

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

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2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: N/A

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3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

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4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

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5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: The paper under discussion is indeed quite intriguing and contributes significantly to the field of Question Answering (QA) Natural Language Processing (NLP). However, there are some areas where the authors can make improvements to enhance the overall quality and clarity of their work:

1. Visualization Choice and Accessibility:

The usage of word clouds in scientific works is not very common nowadays. It is advisable to replace them with more informative and visually accessible alternatives. Options such as Term Frequency-Inverse Document Frequency (TF-IDF) representations, t-Distributed Stochastic Neighbor Embedding (t-SNE), or topic modeling could provide richer insights. Moreover, it's important to ensure that the chosen visualizations are color-blind friendly to make the paper accessible to a wider audience. Lastly, it's essential that the visualizations effectively convey the intended message.

2. Figure Quality and Explanations:

The figures in the paper need to be improved. They lack informative captions, making it challenging for readers to understand their content. It's crucial to provide clear and concise explanations for each figure, including details on how certain metrics, like lexical count in Figure 8 or the measurement of syntactic and semantic dimensions, were derived. Authors should briefly describe the techniques or methodologies employed to calculate these measures, making it easier for readers to replicate or understand the experiments.

3. Dataset Schema:

Including the schema of the dataset in a JSON or similar format would be beneficial. This would provide readers with a clearer understanding of the data used in the experiments and help them better interpret the results.

4. Explanation of LIME Evaluations:

The paper should offer an intuitive explanation of LIME (Local Interpretable Model-agnostic Explanations) evaluations. This will help readers comprehend the significance and implications of using LIME in the context of QA NLP work. Additionally, it's advisable to reference related works like https://doi.org/10.1186/s12859-022-04751-6

in the literature that discuss the use of QA and NLP evaluation.

5. Benchmark Choice:

The authors should provide a clear rationale for choosing RoBERTa as the benchmark model. Explaining why RoBERTa was selected over other models can help readers understand the motivations behind this choice and the implications for the study. Additionally, it would be valuable to mention whether the QA systems were evaluated using exact match metrics or similarity metrics based on BERT or other models.

6. Data Quality Section:

While the paper briefly touches on data quality concerns, it would be beneficial to have a dedicated section that thoroughly addresses data quality issues. This can include discussions any potential biases in the dataset or annotators biases and how it is dealth. Providing this information will enhance the transparency and credibility of the research.

Please proof read the paper again and bring quality figures with captions and how these are made (used some techniques like for visual?)

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6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: Yes: Shaina Raza

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While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

Revision 1

Dear Editor,

Thank you for considering our manuscript and for providing us with the opportunity to revise and resubmit it to PLOS ONE. We are grateful for the valuable feedback received from you and the reviewers. We believe that addressing these comments will greatly enhance the clarity, depth, and overall quality of our work.

We have carefully reviewed each point raised and have undertaken significant revisions to our manuscript to address the concerns highlighted. In particular, we have paid close attention to the comments from point three onwards, as per your recommendation. We have addressed each specific comment made by the reviewers and editor in our detailed 'Response to Reviewers' document, ensuring that our manuscript meets the high standards of PLOS ONE.

In response to the editorial feedback, we have included a comprehensive legend for Figure 1, providing a clear and concise description of its contents and significance in relation to our study. This addition aims to enhance the figure's understanding and ensure its alignment with the manuscript's narrative.

In accordance with the submission guidelines, upon resubmitting our revised manuscript by the specified deadline, we will provide the following items:

• Rebuttal Letter: A detailed letter responding to each point raised by the academic editor and reviewers. This document will be uploaded as a separate file labeled 'Response to Reviewers'.

• Marked-Up Manuscript: A copy of our manuscript with track changes, highlighting the revisions made. This document will be uploaded as a separate file labeled 'Revised Manuscript with Track Changes'.

• Unmarked Manuscript: An unmarked version of the revised paper without tracked changes. This document will be uploaded as a separate file labeled 'Manuscript'.

We are committed to enhancing the reproducibility and transparency of our research and appreciate the guidance provided by PLOS ONE in this process.

Thank you for bringing to our attention the potential citation advantage associated with depositing data in a repository, as highlighted in your recent publication (https://doi.org/10.1371/journal.pone.0230416). We greatly appreciate this valuable insight and the opportunity to enhance the impact and accessibility of our research.

Data Repository Deposition:

We are pleased to announce the deposition of our raw data in a GitHub repository, adhering to PLOS's open data policies. This initiative underscores our commitment to open science by ensuring our data is accessible to the research community. The dataset can be found at https://github.com/mahsamb/FSQD, and the code related to our figures and model is at: https://github.com/mahsamb/FSQD/blob/main/Figures.ipynb.

We look forward to the opportunity to contribute to the PLOS ONE community and thank you again for your valuable feedback. Please do not hesitate to contact us if further information or clarification is required in the meantime.

Kind regards,

Dr. Afsaneh Fatemi

Attachments
Attachment
Submitted filename: Response to Reviewers.docx
Decision Letter - John Blake, Editor

Creating and Validating the Fine-Grained Question Subjectivity Dataset (FSQD): a new benchmark for enhanced Automatic Subjective Question Answering systems

PONE-D-23-33628R1

Dear Dr. Fatemi,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

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If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

Kind regards,

John Blake, PhD

Academic Editor

PLOS ONE

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: All comments have been addressed

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2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Partly

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3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: N/A

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4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

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5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: Most comments are addressed

Figures can be enchanced.

Details for data should be mentioned .

Authors should highlight the contribution in abstract too

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7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

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Formally Accepted
Acceptance Letter - John Blake, Editor

PONE-D-23-33628R1

PLOS ONE

Dear Dr. Fatemi,

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now being handed over to our production team.

At this stage, our production department will prepare your paper for publication. This includes ensuring the following:

* All references, tables, and figures are properly cited

* All relevant supporting information is included in the manuscript submission,

* There are no issues that prevent the paper from being properly typeset

If revisions are needed, the production department will contact you directly to resolve them. If no revisions are needed, you will receive an email when the publication date has been set. At this time, we do not offer pre-publication proofs to authors during production of the accepted work. Please keep in mind that we are working through a large volume of accepted articles, so please give us a few weeks to review your paper and let you know the next and final steps.

Lastly, if your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

If we can help with anything else, please email us at customercare@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. John Blake

Academic Editor

PLOS ONE

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