Create eu_debates.py

eu_debates.py

@@ -0,0 +1,112 @@
+"""EU Debates"""
+
+import json
+import os
+import textwrap
+
+import datasets
+
+
+MAIN_CITATION = """
+@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
+ Stephanie Brandl",
+ booktitle = "Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics",
+ month = jun,
+ year = "2021",
+ address = "Mexico City, Mexico",
+ publisher = "Association for Computational Linguistics",
+}
+"""
+
+_DESCRIPTION = """
+EU Debates is a corpus of parliamentary proceedings (debates) from the EU parliament. The corpus consists of approx. 87k individual speeches in the period 2009-2023. 
+We exhaustively scrape the data from the official European Parliament Plenary website. All speeches are time-stamped, thematically organized on debates, 
+and include metadata relevant to the speaker's identity (full name, euro-party affiliation, speaker role), and the debate (date and title). 
+Older debate speeches are originally in English, while newer ones are linguistically diverse across the 23 official EU languages, thus we also provide machine-translated 
+versions in English, when official translations are missing. 
+"""
+MAIN_PATH = 'https://huggingface.co/datasets/coastalcph/eu_debates/resolve/main'
+
+
+class EUDebatesConfig(datasets.BuilderConfig):
+ """BuilderConfig for EU Debates"""
+
+ def __init__(
+ self,
+ data_url,
+ citation,
+ **kwargs,
+ ):
+ """BuilderConfig for EU Debates.
+
+ Args:
+ data_url: `string`, url to download the zip file from
+ data_file: `string`, filename for data set
+ url: `string`, url for information about the data set
+ **kwargs: keyword arguments forwarded to super.
+ """
+ super(EUParliamentsConfig, self).__init__(version=datasets.Version("1.0.0", ""), **kwargs)
+ self.data_url = data_url
+ self.citation = citation
+
+
+class EUDebates(datasets.GeneratorBasedBuilder):
+ """N/A. Version 1.0"""
+
+ BUILDER_CONFIGS = [
+ EUParliamentsConfig(
+ name="eu",
+ data_url=os.path.join(MAIN_PATH, "eu_parliament.zip"),
+ citation=textwrap.dedent(
+ """N/A"""
+ ),
+ ),
+ ]
+
+ def _info(self):
+ features = {"text": datasets.Value("string"),
+ "translated_text": datasets.Value("string"),
+ "speaker_party": datasets.Value("string"),
+ "speaker_role": datasets.Value("string"),
+ "speaker_name": datasets.Value("string"),
+ "debate_title": datasets.Value("string"),
+ "date": datasets.Value("string"),
+ "year": datasets.Value("string")}
+ return datasets.DatasetInfo(
+ description=self.config.description,
+ features=datasets.Features(features),
+ homepage='https://www.europarl.europa.eu/',
+ citation=MAIN_CITATION,
+ )
+
+ def _split_generators(self, dl_manager):
+ data_dir = dl_manager.download_and_extract(self.config.data_url)
+ return [
+ datasets.SplitGenerator(
+ name=datasets.Split.TRAIN,
+ # These kwargs will be passed to _generate_examples
+ gen_kwargs={
+ "filepath": os.path.join(data_dir, f"train.jsonl"),
+ "split": "train",
+ },
+ ),
+ ]
+
+ def _generate_examples(self, filepath, split):
+ """This function returns the examples."""
+ with open(filepath, encoding="utf-8") as f:
+ for id_, row in enumerate(f):
+ data = json.loads(row)
+ example = {
+ "text": data["text"],
+ "translated_text": data["translated_text"],
+ "speaker_party": data["speaker_party"],
+ "speaker_role": data["speaker_role"],
+ "speaker_name": data["speaker_name"],
+ "debate_title": data["debate_title"],
+ "date": data["date"],
+ "year": data["year"]
+ }
+ yield id_, example