References:
books
Use the following command to load this dataset in TFDS:
ds = tfds.load('huggingface:subjqa/books')
- Description:
SubjQA is a question answering dataset that focuses on subjective questions and answers.
The dataset consists of roughly 10,000 questions over reviews from 6 different domains: books, movies, grocery,
electronics, TripAdvisor (i.e. hotels), and restaurants.
- License: No known license
- Version: 1.1.0
- Splits:
| Split | Examples |
|---|---|
'test' |
345 |
'train' |
1314 |
'validation' |
256 |
- Features:
{
"domain": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"nn_mod": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"nn_asp": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"query_mod": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"query_asp": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"q_reviews_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"question_subj_level": {
"dtype": "int64",
"id": null,
"_type": "Value"
},
"ques_subj_score": {
"dtype": "float32",
"id": null,
"_type": "Value"
},
"is_ques_subjective": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"review_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"title": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"context": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answers": {
"feature": {
"text": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer_start": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"answer_subj_level": {
"dtype": "int64",
"id": null,
"_type": "Value"
},
"ans_subj_score": {
"dtype": "float32",
"id": null,
"_type": "Value"
},
"is_ans_subjective": {
"dtype": "bool",
"id": null,
"_type": "Value"
}
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
electronics
Use the following command to load this dataset in TFDS:
ds = tfds.load('huggingface:subjqa/electronics')
- Description:
SubjQA is a question answering dataset that focuses on subjective questions and answers.
The dataset consists of roughly 10,000 questions over reviews from 6 different domains: books, movies, grocery,
electronics, TripAdvisor (i.e. hotels), and restaurants.
- License: No known license
- Version: 1.1.0
- Splits:
| Split | Examples |
|---|---|
'test' |
358 |
'train' |
1295 |
'validation' |
255 |
- Features:
{
"domain": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"nn_mod": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"nn_asp": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"query_mod": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"query_asp": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"q_reviews_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"question_subj_level": {
"dtype": "int64",
"id": null,
"_type": "Value"
},
"ques_subj_score": {
"dtype": "float32",
"id": null,
"_type": "Value"
},
"is_ques_subjective": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"review_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"title": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"context": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answers": {
"feature": {
"text": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer_start": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"answer_subj_level": {
"dtype": "int64",
"id": null,
"_type": "Value"
},
"ans_subj_score": {
"dtype": "float32",
"id": null,
"_type": "Value"
},
"is_ans_subjective": {
"dtype": "bool",
"id": null,
"_type": "Value"
}
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
grocery
Use the following command to load this dataset in TFDS:
ds = tfds.load('huggingface:subjqa/grocery')
- Description:
SubjQA is a question answering dataset that focuses on subjective questions and answers.
The dataset consists of roughly 10,000 questions over reviews from 6 different domains: books, movies, grocery,
electronics, TripAdvisor (i.e. hotels), and restaurants.
- License: No known license
- Version: 1.1.0
- Splits:
| Split | Examples |
|---|---|
'test' |
591 |
'train' |
1124 |
'validation' |
218 |
- Features:
{
"domain": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"nn_mod": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"nn_asp": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"query_mod": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"query_asp": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"q_reviews_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"question_subj_level": {
"dtype": "int64",
"id": null,
"_type": "Value"
},
"ques_subj_score": {
"dtype": "float32",
"id": null,
"_type": "Value"
},
"is_ques_subjective": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"review_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"title": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"context": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answers": {
"feature": {
"text": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer_start": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"answer_subj_level": {
"dtype": "int64",
"id": null,
"_type": "Value"
},
"ans_subj_score": {
"dtype": "float32",
"id": null,
"_type": "Value"
},
"is_ans_subjective": {
"dtype": "bool",
"id": null,
"_type": "Value"
}
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
movies
Use the following command to load this dataset in TFDS:
ds = tfds.load('huggingface:subjqa/movies')
- Description:
SubjQA is a question answering dataset that focuses on subjective questions and answers.
The dataset consists of roughly 10,000 questions over reviews from 6 different domains: books, movies, grocery,
electronics, TripAdvisor (i.e. hotels), and restaurants.
- License: No known license
- Version: 1.1.0
- Splits:
| Split | Examples |
|---|---|
'test' |
291 |
'train' |
1369 |
'validation' |
261 |
- Features:
{
"domain": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"nn_mod": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"nn_asp": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"query_mod": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"query_asp": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"q_reviews_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"question_subj_level": {
"dtype": "int64",
"id": null,
"_type": "Value"
},
"ques_subj_score": {
"dtype": "float32",
"id": null,
"_type": "Value"
},
"is_ques_subjective": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"review_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"title": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"context": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answers": {
"feature": {
"text": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer_start": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"answer_subj_level": {
"dtype": "int64",
"id": null,
"_type": "Value"
},
"ans_subj_score": {
"dtype": "float32",
"id": null,
"_type": "Value"
},
"is_ans_subjective": {
"dtype": "bool",
"id": null,
"_type": "Value"
}
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
restaurants
Use the following command to load this dataset in TFDS:
ds = tfds.load('huggingface:subjqa/restaurants')
- Description:
SubjQA is a question answering dataset that focuses on subjective questions and answers.
The dataset consists of roughly 10,000 questions over reviews from 6 different domains: books, movies, grocery,
electronics, TripAdvisor (i.e. hotels), and restaurants.
- License: No known license
- Version: 1.1.0
- Splits:
| Split | Examples |
|---|---|
'test' |
266 |
'train' |
1400 |
'validation' |
267 |
- Features:
{
"domain": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"nn_mod": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"nn_asp": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"query_mod": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"query_asp": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"q_reviews_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"question_subj_level": {
"dtype": "int64",
"id": null,
"_type": "Value"
},
"ques_subj_score": {
"dtype": "float32",
"id": null,
"_type": "Value"
},
"is_ques_subjective": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"review_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"title": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"context": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answers": {
"feature": {
"text": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer_start": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"answer_subj_level": {
"dtype": "int64",
"id": null,
"_type": "Value"
},
"ans_subj_score": {
"dtype": "float32",
"id": null,
"_type": "Value"
},
"is_ans_subjective": {
"dtype": "bool",
"id": null,
"_type": "Value"
}
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
tripadvisor
Use the following command to load this dataset in TFDS:
ds = tfds.load('huggingface:subjqa/tripadvisor')
- Description:
SubjQA is a question answering dataset that focuses on subjective questions and answers.
The dataset consists of roughly 10,000 questions over reviews from 6 different domains: books, movies, grocery,
electronics, TripAdvisor (i.e. hotels), and restaurants.
- License: No known license
- Version: 1.1.0
- Splits:
| Split | Examples |
|---|---|
'test' |
512 |
'train' |
1165 |
'validation' |
230 |
- Features:
{
"domain": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"nn_mod": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"nn_asp": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"query_mod": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"query_asp": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"q_reviews_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"question_subj_level": {
"dtype": "int64",
"id": null,
"_type": "Value"
},
"ques_subj_score": {
"dtype": "float32",
"id": null,
"_type": "Value"
},
"is_ques_subjective": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"review_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"title": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"context": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answers": {
"feature": {
"text": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer_start": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"answer_subj_level": {
"dtype": "int64",
"id": null,
"_type": "Value"
},
"ans_subj_score": {
"dtype": "float32",
"id": null,
"_type": "Value"
},
"is_ans_subjective": {
"dtype": "bool",
"id": null,
"_type": "Value"
}
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}