RJuro/eu_debates

Dataset Description

This dataset is a conversion of the original coastalcph/eu_debates dataset released by Chalkidis and Brandl (2024).

The goal of this repository is to provide the same underlying data without a Python loading script, in a standard format (JSON Lines / Parquet) compatible with the current Hugging Face datasets library and automated data loading.

The original EU Debates corpus consists of approx. 87k individual speeches in the period 2009–2023. The data was exhaustively scraped from the official European Parliament Plenary website (link). All speeches are time-stamped, thematically organized in debates, and include metadata about:

• the speaker's identity (full name, euro-party affiliation, speaker role),
• the debate (date and title),
• language information, and (where available) machine-translated versions in English.

Older debate speeches are originally in English, while newer ones are linguistically diverse across the 23 official EU languages. Machine-translated English versions are provided using the EasyNMT framework with the M2M-100 (418M) model (Fan et al., 2020).

This repository only changes the storage format (to train.jsonl / Parquet) and removes the Python loading script. The data contents and fields are preserved from the original dataset.

Data Fields

Each row / JSONL line is a single speech with the following fields:

• speaker_name: string, full name of the speaker.
• speaker_party: string, name of the euro-party (group) that the MEP is affiliated with.
• speaker_role: string, role of the speaker (e.g., Member of the European Parliament (MEP), EUROPARL President).
• debate_title: string, title of the debate in the European Parliament.
• date: string, full date of the speech in YYYY-MM-DD format.
• year: string, year of the speech in YYYY format.
• intervention_language: string, language code of the original intervention.
• original_language: string, language code of the original text.
• text: string, full original speech of the speaker.
• translated_text: string or null, machine translation of the speech into English if the original is not English, otherwise null.

Data Instances

Example of a data instance:

{
  "speaker_name": "Michèle Striffler",
  "speaker_party": "PPE",
  "speaker_role": "MEP",
  "debate_title": "Famine in East Africa (debate)",
  "date": "2011-09-15",
  "year": "2011",
  "intervention_language": "fr",
  "original_language": "fr",
  "text": "Monsieur le Président, Madame le Commissaire, chers collègues, la situation humanitaire sans précédent que connaît la Corne de l'Afrique continue [...]",
  "translated_text": "Mr. President, Mr. Commissioner, dear colleagues, the unprecedented humanitarian situation of the Horn of Africa continues [...]"
}

How to Use

From the Hugging Face Hub

If the dataset is hosted under RJuro/eu_debates:

from datasets import load_dataset

eu_debates = load_dataset("RJuro/eu_debates", split="train")

From Local Files

If you downloaded the train.jsonl file locally:

from datasets import load_dataset

eu_debates = load_dataset(
    "json",
    data_files={"train": "train.jsonl"},
    split="train",
)

If you use Parquet instead:

from datasets import load_dataset

eu_debates = load_dataset(
    "parquet",
    data_files={"train": "train.parquet"},
    split="train",
)

Dataset Statistics

The statistics below are inherited from the original coastalcph/eu_debates dataset.

Distribution of speeches across euro-parties:

Euro-party	No. of Speeches
EPP	25,455 (29%)
S&D	20,042 (23%)
ALDE	8,946 (10%)
ECR	7,493 (9%)
ID	6,970 (8%)
GUE/NGL	6,780 (8%)
Greens/EFA	6,398 (7%)
NI	5,127 (6%)
Total	87,221

Distribution of speeches across years and euro-parties:

Year	EPP	S&D	ALDE	ECR	ID	GUE/NGL	Greens/EFA	NI	Total
2009	748	456	180	138	72	174	113	163	2044
2010	3205	1623	616	340	341	529	427	546	7627
2011	4479	2509	817	418	761	792	490	614	10880
2012	3366	1892	583	419	560	486	351	347	8004
2013	724	636	240	175	152	155	170	154	2406
2014	578	555	184	180	131	160	144	180	2112
2015	978	1029	337	405	398	325	246	240	3958
2016	919	972	309	387	457	317	225	151	3737
2017	649	766	181	288	321	229	162	135	2731
2018	554	611	161	242	248	175	160	133	2284
2019	1296	1339	719	556	513	463	490	353	5729
2020	1660	1564	823	828	661	526	604	346	7012
2021	2147	2189	1290	1062	909	708	990	625	9920
2022	2436	2273	1466	1177	827	962	1031	641	10813
2023	1716	1628	1040	878	619	779	795	499	7954

Distribution of speeches across the 23 EU official languages:

Language	No. of Speeches
en	40,736 (46.7%)
de	6,497 (7.5%)
fr	6,024 (6.9%)
es	5,172 (5.9%)
it	4,506 (5.2%)
pl	3,792 (4.4%)
pt	2,713 (3.1%)
ro	2,308 (2.7%)
el	2,290 (2.6%)
nl	2,286 (2.6%)
hu	1,661 (1.9%)
hr	1,509 (1.7%)
cs	1,428 (1.6%)
sv	1,210 (1.4%)
bg	928 (1.1%)
sk	916 (1.1%)
sl	753 (0.9%)
fi	693 (0.8%)
lt	618 (0.7%)
da	578 (0.7%)
et	342 (0.4%)
lv	184 (0.2%)
mt	0 (0.0%)

Citation Information

If you use this dataset, please cite the original work:

Llama meets EU: Investigating the European political spectrum through the lens of LLMs. Ilias Chalkidis and Stephanie Brandl. In the Proceedings of the Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL), Mexico City, Mexico, June 16–21, 2024.

@inproceedings{chalkidis-and-brandl-eu-llama-2024,
    title = "Llama meets EU: Investigating the European political spectrum through the lens of LLMs",
    author = "Chalkidis, Ilias  and Brandl, Stephanie",
    booktitle = "Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics",
    month = jun,
    year = "2024",
    address = "Mexico City, Mexico",
    publisher = "Association for Computational Linguistics",
}

This repository only provides a format-converted, script-free version of the original dataset; all credit for data collection and annotation goes to the original authors.