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- # Dataset Card for EuroParlVote
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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- ## Dataset Details
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- ### Dataset Description
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- EuroParlVote links **European Parliament debate speeches** to **roll-call votes** and **Member of European Parliament (MEP) demographic data** across up to 24 official EU languages.
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- It supports two primary benchmark tasks:
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- 1. **Gender Classification**: Predict the MEP’s gender from a debate speech.
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- 2. **Vote Prediction**: Predict a FOR/AGAINST vote from the topic and speech (optionally with demographic context).
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- This dataset is based on publicly available EP plenary records and enhanced with metadata scraped from Wikipedia and other official sources.
 
 
 
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  - **Curated by:** Jinrui Yang, Xudong Han, Timothy Baldwin
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  - **Funded by:** Melbourne Research Scholarship; LIEF HPC-GPGPU Facility (LE170100200)
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- - **Shared by:** University of Melbourne
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- - **Language(s) (NLP):** Up to 24 official EU languages (Language column)
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- - **License:** CC BY-NC 4.0 (to confirm)
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  ### Dataset Sources
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+ dataset_name: europarlvote
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+ pretty_name: EuroParlVote
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+ paperswithcode_id: null
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+ task_categories:
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+ - text-classification
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+ tasks:
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+ - gender-classification
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+ - stance-detection
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+ - vote-prediction
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+ multilinguality: multilingual
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+ language:
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+ - bg
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+ - cs
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+ - da
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+ - de
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+ - el
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+ - en
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+ - es
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+ - et
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+ - fi
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+ - fr
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+ - ga
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+ - hr
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+ - hu
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+ - it
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+ - lt
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+ - lv
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+ - mt
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+ - nl
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+ - pl
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+ - pt
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+ - ro
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+ - sk
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+ - sl
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+ - sv
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+ license: cc-by-nc-4.0
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+ size_categories:
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+ - 10K<n<100K
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+ annotations_creators:
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+ - expert-generated
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+ source_datasets:
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+ - original
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+ domain:
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+ - politics
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+ - public-policy
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+ demographics:
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+ - adult
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+ - public-figures
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+ creators:
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+ - Jinrui Yang
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+ - Xudong Han
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+ - Timothy Baldwin
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+ maintainers:
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+ - Jinrui Yang <[email protected]>
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+ ---
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+ # EuroParlVote
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+ EuroParlVote links **European Parliament debate speeches** to **roll-call votes** and **MEP demographics** (gender, age, country, political group) across up to **24 EU languages**.
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+ It supports two primary benchmark tasks:
 
 
 
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+ 1. **Gender Classification** predict the MEP’s gender from a debate speech.
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+ 2. **Vote Prediction** – predict a FOR/AGAINST vote from the topic and speech (optionally with demographic context).
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+
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+ ## Dataset Details
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  - **Curated by:** Jinrui Yang, Xudong Han, Timothy Baldwin
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  - **Funded by:** Melbourne Research Scholarship; LIEF HPC-GPGPU Facility (LE170100200)
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+ - **Shared by:** University of Melbourne
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+ - **Language(s):** see list above (`language`)
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+ - **License:** CC BY-NC 4.0
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  ### Dataset Sources
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