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---
license: mit
task_categories:
- text-generation
language:
- en
size_categories:
- 100K<n<1M
---
# IEA_Energy_Dataset
## Dataset Details
### Dataset Description
The dataset is energy-related, covering topics of **Oil**, **Coal**, **Wind**, **Hydrogen**, **Bioenergy**, **Electric vehicles**, **Heating**, **Building envelopes**, **Methane abatement** and **Chemicals**.
## Dataset Creation
### Source Data
The dataset sources are reports from the webiste of [International Energy Agency(IEA)]('https://www.iea.org/').
### Data Collection and Processing
We scraped free open reports from [IEA's website]("https://www.iea.org/analysis"). The reports are all pdf files and then we used the Llama 3 model to extract useful texts.\
After getting the raw text, we have the two following steps:
1. Remove too short sentences(e.g length < 100)
2. Use [Monocleaner]('https://github.com/bitextor/monocleaner') to detect disfluent sentences. Each sentence will have a score(0~1), and then we set a threshold to filter.
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