|
|
--- |
|
|
license: apache-2.0 |
|
|
language: |
|
|
- en |
|
|
size_categories: |
|
|
- n<1K |
|
|
task_categories: |
|
|
- question-answering |
|
|
configs: |
|
|
- config_name: benchmark |
|
|
data_files: |
|
|
- split: test |
|
|
path: dataset.json |
|
|
tags: |
|
|
- geospatial |
|
|
annotations_creators: |
|
|
- expert-generated |
|
|
paperswithcode_id: mapeval-textual |
|
|
--- |
|
|
|
|
|
|
|
|
# MapEval-Textual |
|
|
|
|
|
[MapEval](https://arxiv.org/abs/2501.00316)-Textual is created using [MapQaTor](https://arxiv.org/abs/2412.21015). |
|
|
|
|
|
## Usage |
|
|
|
|
|
```python |
|
|
from datasets import load_dataset |
|
|
|
|
|
# Load dataset |
|
|
ds = load_dataset("MapEval/MapEval-Textual", name="benchmark") |
|
|
|
|
|
# Generate better prompts |
|
|
for item in ds["test"]: |
|
|
# Start with a clear task description |
|
|
prompt = ( |
|
|
"You are a highly intelligent assistant. " |
|
|
"Based on the given context, answer the multiple-choice question by selecting the correct option.\n\n" |
|
|
"Context:\n" + item["context"] + "\n\n" |
|
|
"Question:\n" + item["question"] + "\n\n" |
|
|
"Options:\n" |
|
|
) |
|
|
|
|
|
# List the options more clearly |
|
|
for i, option in enumerate(item["options"], start=1): |
|
|
prompt += f"{i}. {option}\n" |
|
|
|
|
|
# Add a concluding sentence to encourage selection of the answer |
|
|
prompt += "\nSelect the best option by choosing its number." |
|
|
|
|
|
# Use the prompt as needed |
|
|
print(prompt) # Replace with your processing logic |
|
|
``` |
|
|
|