metadata
{}
AutoTrain Dataset for project: my-qa
Dataset Description
This dataset has been automatically processed by AutoTrain for project my-qa.
Languages
The BCP-47 code for the dataset's language is unk.
Dataset Structure
Data Instances
A sample from this dataset looks as follows:
[
{
"context": "Candidates, whose selection is recommended by the DRC and approved by Chairman Senate, shall be offered admission and advised to deposit the prescribed fee. After depositing the fee, he/she shall be designated as \ufffdPhD Scholar (PS)\ufffd. For all purposes, the date of registration of a PS shall be the date on which he/she has deposited the fee in the institute. After registration, Research Advisory Committees (RACs) for the individual PS shall be constituted by the concerned Head of the Department in consultation with the Sup",
"question": "Who is PS?",
"answers.text": [
"PhD Scholar"
],
"answers.answer_start": [
214
],
"feat_answer_id": [
955042
],
"feat_document_id": [
1586827
],
"feat_question_id": [
1066405
],
"feat_answer_end": [
225
],
"feat_answer_category": [
null
],
"feat_file_name": [
null
]
},
{
"context": " Indian Council of Cultural Relations, Govt. of India, are eligible to apply provided that they possess the same minimum qualifications as Master\ufffds Degree in Engineering/Technology in the relevant area of research along with a Bachelor\ufffds Degree in an appropriate branch of Engineering/Technology with first-class or minimum 60% marks (or CGPA of 6.5 on a 10-point scale or equivalent) at Master\ufffds and Bachelor\ufffds level. Master\ufffds Degree in an appropriate branch of Science/Humanities/Social Sciences/Management with a first-class or minimum 60% marks (or CGPA of 6.5 on a 10-point scale or equivalent) or equivalen",
"question": "What class is required for Foreign National candidates in Ph.D.?",
"answers.text": [
" first-class"
],
"answers.answer_start": [
409
],
"feat_answer_id": [
955615
],
"feat_document_id": [
1586816
],
"feat_question_id": [
1066345
],
"feat_answer_end": [
421
],
"feat_answer_category": [
null
],
"feat_file_name": [
null
]
}
]
Dataset Fields
The dataset has the following fields (also called "features"):
{
"context": "Value(dtype='string', id=None)",
"question": "Value(dtype='string', id=None)",
"answers.text": "Sequence(feature=Value(dtype='string', id=None), length=-1, id=None)",
"answers.answer_start": "Sequence(feature=Value(dtype='int32', id=None), length=-1, id=None)",
"feat_answer_id": "Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None)",
"feat_document_id": "Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None)",
"feat_question_id": "Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None)",
"feat_answer_end": "Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None)",
"feat_answer_category": "Sequence(feature=Value(dtype='null', id=None), length=-1, id=None)",
"feat_file_name": "Sequence(feature=Value(dtype='null', id=None), length=-1, id=None)"
}
Dataset Splits
This dataset is split into a train and validation split. The split sizes are as follow:
| Split name | Num samples |
|---|---|
| train | 63 |
| valid | 16 |