README.md

---
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"}`