20 extractive question-and-answer pairs built from Graduate Admission 2 | Kaggle, published by kaggle.com. Every answer is a verbatim span of text the source prints, and each row carries the passage it sits in, its offset in that passage, the source quote, the page and the location in the document, so any row can be checked against the original. 14 of the 20 pairs (70.0%) are explanatory questions and 6 restate a figure. 100.00% of rows pass the corpus quality gate.
Use the API URL with your free DD token in notebooks, scripts, and pipelines.
https://www.desidata.in/api/datasets/graduate-admission-2-question-and-answer-dataset/downloadDataset downloads are free. For Python or API downloads, sign in once and create a free DD token; set it as DD_TOKEN or save it in your notebook's secrets. Requests are linked to your account so your download history and counts stay accurate.
# One-time install: pip install desidata
# Set DD_TOKEN in your environment first (create a free token in Profile & settings).
import desidata
df = desidata.load("graduate-admission-2-question-and-answer-dataset")
df.head()Sign in with Google to download.
Usable for analysis, but expect some cleaning before you rely on it.
Annual Report 2015-16 by agriwelfare.gov.in - Question and Answer Dataset
Economy · 1,013 rows
Higher Education in India - Question and Answer Dataset
Economy · 1,594 rows
Gender Policy of NABARD - Question and Answer Dataset
Economy · 14 rows
ICAR Annual Report 2025-26 - Question and Answer Dataset
Economy · 1,101 rows
First 10 of 20 rows
| question | answer | context | answer_start | question_type | knowledge_quality_score | source_quote | source_page | source_location | confidence | validation_status |
|---|---|---|---|---|---|---|---|---|---|---|
| What is the goal of the Graduate Admission 2 dataset? | prediction of Graduate Admissions from an Indian perspective. | Graduate Admission 2 | Kaggle Graduate Admission 2 ### Context This dataset is created for prediction of Graduate Admissions from an Indian perspective. ### Content The dataset contains several parameters which are considered important during the application for Masters Programs. The parameters included are : 1. GRE Scores ( out of 340 ) 2. TOEFL Scores ( out of 120 ) 3. University Rating ( out of 5 ) 4. Statement of Purpose and Letter of Recommendation Strength ( out of 5 ) 5. Undergraduate GPA ( out of 10 ) 6. Research Experience ( either 0 or 1 ) 7. Chance of Admit ( ranging from 0 to 1 ) ### Acknowledgements This dataset is inspired by the UCLA Graduate Dataset. The test scores and GPA are in the older format. The dataset is owned by Mohan S Acharya. ### Inspiration This dataset was built with the purpose of helping students in shortlisting universities with their profiles. | 91 | summary | 0.970 | Graduate Admission 2 | Kaggle Graduate Admission 2 ### Context This dataset is created for prediction of Graduate Admissions from an Indian perspective. ### Content The dataset contains several parameters which are considered important during the application for Masters Programs. | title | 0.700 | valid | |
| What is the purpose of the dataset in assisting students? | helping students in shortlisting universities with their profiles. | Graduate Admission 2 | Kaggle Graduate Admission 2 ### Context This dataset is created for prediction of Graduate Admissions from an Indian perspective. ### Content The dataset contains several parameters which are considered important during the application for Masters Programs. The parameters included are : 1. GRE Scores ( out of 340 ) 2. TOEFL Scores ( out of 120 ) 3. University Rating ( out of 5 ) 4. Statement of Purpose and Letter of Recommendation Strength ( out of 5 ) 5. Undergraduate GPA ( out of 10 ) 6. Research Experience ( either 0 or 1 ) 7. Chance of Admit ( ranging from 0 to 1 ) ### Acknowledgements This dataset is inspired by the UCLA Graduate Dataset. The test scores and GPA are in the older format. The dataset is owned by Mohan S Acharya. ### Inspiration This dataset was built with the purpose of helping students in shortlisting universities with their profiles. | 824 | summary | 0.970 | ### Inspiration This dataset was built with the purpose of helping students in shortlisting universities with their profiles. | title | 0.700 | valid | |
| What is the purpose of the Graduate Admission 2 dataset? | prediction of Graduate Admissions from an Indian perspective. | Graduate Admission 2 | Kaggle Graduate Admission 2 ### Context This dataset is created for prediction of Graduate Admissions from an Indian perspective. ### Content The dataset contains several parameters which are considered important during the application for Masters Programs. The parameters included are : 1. GRE Scores ( out of 340 ) 2. TOEFL Scores ( out of 120 ) 3. University Rating ( out of 5 ) 4. Statement of Purpose and Letter of Recommendation Strength ( out of 5 ) 5. Undergraduate GPA ( out of 10 ) 6. Research Experience ( either 0 or 1 ) 7. Chance of Admit ( ranging from 0 to 1 ) ### Acknowledgements This dataset is inspired by the UCLA Graduate Dataset. The test scores and GPA are in the older format. The dataset is owned by Mohan S Acharya. ### Inspiration This dataset was built with the purpose of helping students in shortlisting universities with their profiles. | 91 | summary | 0.970 | Graduate Admission 2 | Kaggle Graduate Admission 2 ### Context This dataset is created for prediction of Graduate Admissions from an Indian perspective. ### Content The dataset contains several parameters which are considered important during the application for Masters Programs. | ||||
| What is the purpose of building the Graduate Admission 2 dataset? | helping students in shortlisting universities with their profiles. | Graduate Admission 2 | Kaggle Graduate Admission 2 ### Context This dataset is created for prediction of Graduate Admissions from an Indian perspective. ### Content The dataset contains several parameters which are considered important during the application for Masters Programs. The parameters included are : 1. GRE Scores ( out of 340 ) 2. TOEFL Scores ( out of 120 ) 3. University Rating ( out of 5 ) 4. Statement of Purpose and Letter of Recommendation Strength ( out of 5 ) 5. Undergraduate GPA ( out of 10 ) 6. Research Experience ( either 0 or 1 ) 7. Chance of Admit ( ranging from 0 to 1 ) ### Acknowledgements This dataset is inspired by the UCLA Graduate Dataset. The test scores and GPA are in the older format. The dataset is owned by Mohan S Acharya. ### Inspiration This dataset was built with the purpose of helping students in shortlisting universities with their profiles. | 824 | summary | 0.970 | ### Inspiration This dataset was built with the purpose of helping students in shortlisting universities with their profiles. | title | 0.700 | valid | |
| What does the predicted output of the dataset provide to users? | a fair idea about their chances for a particular university. | The predicted output gives them a fair idea about their chances for a particular university. ### Citation Please cite the following if you are interested in using the dataset : **Mohan S Acharya, Asfia Armaan, Aneeta S Antony : A Comparison of Regression Models for Prediction of Graduate Admissions, IEEE International Conference on Computational Intelligence in Data Science 2019** I would like to thank all of you for contributing to this dataset through discussions and questions. I am in awe of the number of kernels built on this dataset. Some results and visualisations are fantastic and makes me a proud owner of the dataset. Keep em' coming! Thank You. CC0: Public Domain data type, tabular, subject, people and society, education, universities and colleges, subject, people and society, education, standardized testing, task, regression, task, linear regression | 32 | summary | 0.970 | The predicted output gives them a fair idea about their chances for a particular university. ### Citation Please cite the following if you are interested in using the dataset : **Mohan S Acharya, Asfia Armaan, Aneeta S Antony : A Comparison of Regression Models for Prediction of Graduate Admissions, IEEE International Conference on Computational Intelligence in Data Science 2019** I would like to thank all of you for contributing to this dataset through discussions and questions. | ||||
| What does the predicted output of the dataset provide to students? | a fair idea about their chances for a particular university. | The predicted output gives them a fair idea about their chances for a particular university. ### Citation Please cite the following if you are interested in using the dataset : **Mohan S Acharya, Asfia Armaan, Aneeta S Antony : A Comparison of Regression Models for Prediction of Graduate Admissions, IEEE International Conference on Computational Intelligence in Data Science 2019** I would like to thank all of you for contributing to this dataset through discussions and questions. I am in awe of the number of kernels built on this dataset. Some results and visualisations are fantastic and makes me a proud owner of the dataset. Keep em' coming! Thank You. CC0: Public Domain data type, tabular, subject, people and society, education, universities and colleges, subject, people and society, education, standardized testing, task, regression, task, linear regression | 32 | summary | 0.970 | The predicted output gives them a fair idea about their chances for a particular university. ### Citation Please cite the following if you are interested in using the dataset : **Mohan S Acharya, Asfia Armaan, Aneeta S Antony : A Comparison of Regression Models for Prediction of Graduate Admissions, IEEE International Conference on Computational Intelligence in Data Science 2019** I would like to thank all of you for contributing to this dataset through discussions and questions. | ||||
| What type of data is the Graduate Admission dataset classified as? | tabular | The predicted output gives them a fair idea about their chances for a particular university. ### Citation Please cite the following if you are interested in using the dataset : **Mohan S Acharya, Asfia Armaan, Aneeta S Antony : A Comparison of Regression Models for Prediction of Graduate Admissions, IEEE International Conference on Computational Intelligence in Data Science 2019** I would like to thank all of you for contributing to this dataset through discussions and questions. I am in awe of the number of kernels built on this dataset. Some results and visualisations are fantastic and makes me a proud owner of the dataset. Keep em' coming! Thank You. CC0: Public Domain data type, tabular, subject, people and society, education, universities and colleges, subject, people and society, education, standardized testing, task, regression, task, linear regression | 692 | definition | 0.940 | CC0: Public Domain data type, tabular, subject, people and society, education, universities and colleges, subject, people and society, education, standardized testing, task, regression, task, linear regression | title | 0.700 | ||
| What inspired the creation of the Graduate Admission 2 dataset? | the UCLA Graduate Dataset. | Graduate Admission 2 | Kaggle Graduate Admission 2 ### Context This dataset is created for prediction of Graduate Admissions from an Indian perspective. ### Content The dataset contains several parameters which are considered important during the application for Masters Programs. The parameters included are : 1. GRE Scores ( out of 340 ) 2. TOEFL Scores ( out of 120 ) 3. University Rating ( out of 5 ) 4. Statement of Purpose and Letter of Recommendation Strength ( out of 5 ) 5. Undergraduate GPA ( out of 10 ) 6. Research Experience ( either 0 or 1 ) 7. Chance of Admit ( ranging from 0 to 1 ) ### Acknowledgements This dataset is inspired by the UCLA Graduate Dataset. The test scores and GPA are in the older format. The dataset is owned by Mohan S Acharya. ### Inspiration This dataset was built with the purpose of helping students in shortlisting universities with their profiles. | 648 | relationship | 0.890 | Chance of Admit ( ranging from 0 to 1 ) ### Acknowledgements This dataset is inspired by the UCLA Graduate Dataset. The test scores and GPA are in the older format. | title | 0.700 | ||
| What is the source of inspiration for the Graduate Admission 2 dataset? | the UCLA Graduate Dataset | Graduate Admission 2 | Kaggle Graduate Admission 2 ### Context This dataset is created for prediction of Graduate Admissions from an Indian perspective. ### Content The dataset contains several parameters which are considered important during the application for Masters Programs. The parameters included are : 1. GRE Scores ( out of 340 ) 2. TOEFL Scores ( out of 120 ) 3. University Rating ( out of 5 ) 4. Statement of Purpose and Letter of Recommendation Strength ( out of 5 ) 5. Undergraduate GPA ( out of 10 ) 6. Research Experience ( either 0 or 1 ) 7. Chance of Admit ( ranging from 0 to 1 ) ### Acknowledgements This dataset is inspired by the UCLA Graduate Dataset. The test scores and GPA are in the older format. The dataset is owned by Mohan S Acharya. ### Inspiration This dataset was built with the purpose of helping students in shortlisting universities with their profiles. | 648 | relationship | 0.890 | Chance of Admit ( ranging from 0 to 1 ) ### Acknowledgements This dataset is inspired by the UCLA Graduate Dataset. | title | 0.700 | valid | |
| What are the subjects associated with the Graduate Admission dataset? | people and society, education, universities and colleges, subject, people and society, education, standardized testing | The predicted output gives them a fair idea about their chances for a particular university. ### Citation Please cite the following if you are interested in using the dataset : **Mohan S Acharya, Asfia Armaan, Aneeta S Antony : A Comparison of Regression Models for Prediction of Graduate Admissions, IEEE International Conference on Computational Intelligence in Data Science 2019** I would like to thank all of you for contributing to this dataset through discussions and questions. I am in awe of the number of kernels built on this dataset. Some results and visualisations are fantastic and makes me a proud owner of the dataset. Keep em' coming! Thank You. CC0: Public Domain data type, tabular, subject, people and society, education, universities and colleges, subject, people and society, education, standardized testing, task, regression, task, linear regression | 710 | list | 0.820 | CC0: Public Domain data type, tabular, subject, people and society, education, universities and colleges, subject, people and society, education, standardized testing, task, regression, task, linear regression |
Read straight from the file — download or use the API URL for the full dataset.
| title |
| 0.700 |
| valid |
| title |
| 0.700 |
| valid |
| title |
| 0.700 |
| valid |
| valid |
| valid |
| title |
| 0.700 |
| valid |