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---
task_categories:
- sentence-similarity
- feature-extraction
language:
- en
tags:
- biology
- medical
- chemistry
pretty_name: Gooqa Biological Subset
size_categories:
- 10K<n<100K
---
# Dataset Card for GooAQ-Bio
This is a subset of [sentence-transformers/gooaq](https://huggingface.co./datasets/sentence-transformers/gooaq).
This dataset is a collection of question-answer pairs, collected from Google. See GooAQ for additional information. This dataset can be used directly with Sentence Transformers to train embedding models.
## Dataset Subsets
Columns: "question", "answer", "category"
Column types: str, str
Examples:
```
{
'question': 'is toprol xl the same as metoprolol?',
'answer': 'Metoprolol succinate is also known by the brand name Toprol XL. It is the extended-release form of metoprolol. Metoprolol succinate is approved to treat high blood pressure, chronic chest pain, and congestive heart failure.',
'category': 'Medicine'
}
```
## Method of categorization
Llama-3.1-8B was queried for category for each question using the following function:
```python
def get_category(row):
query = "You need to categorize the following question into one of the following categories: "
categories = ["Biology", "Chemistry", "Physics", "Mathematics", "Computer Science", "Medicine", "Pop culture", "History", "Philosophy", "Art", "Music", "Sports", "Politics", "Religion", "Other"]
query += ", ".join(categories)
query += ". The question is: ```" + row["question"] + "```"
query += ". The answer is: ```" + row["answer"] + "```"
query += "\n Answer only with the category name, no other text."
return ask_llm(query)
```
This subset consists only of the following categories: `{"Biology", "Chemistry", "Medicine"}` |