datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
authorship-strategy
Authorship Strategy — Knowledge Graph
JSON-LD knowledge graph encoding the concept layer of the Authorship Strategy research line — a normative framework, tactical catalog, and empirical baseline for authorship strategy under AI-mediated diffusion.
What this dataset is
This dataset is a mirror of the graph.jsonld file at the root of the Authorship Strategy GitHub repository. It is provided here for LLM training pipelines, knowledge-graph crawlers, and AI research… See the full description on the dataset page: https://huggingface.co/datasets/shimo4228/authorship-strategy.authorship-attribution-dataDataset of authorship attribution. Each row has columns base_messages, same_author_messages, and different_author_messages. Each column is a set of 10 messages separated by \n<sep>\n. base_messages and same_author_messages are two sets of non-overlapping messages written by the same author, and different_author_messages is a set of messages written by a randomly selected different author. The columns are set up to make triplet loss training easy to do.
All data is from Discord, and most data… See the full description on the dataset page: https://huggingface.co/datasets/trentmkelly/authorship-attribution-data.amazon-review-authorship-verificationUsage
from datasets import load_dataset
# Load German part of the dataset
dataset = load_dataset("sobamchan/amazon-review-authorship-verification", "de")
print(dataset["train"][0])
# {'review_1': {'language': 'de',
# 'product_category': 'home_improvement',
# 'product_id': 'product_de_0996190',
# 'review_body': 'Trotz diesem Fliegengitter haben ungebetene Gäste Möglicheiten zum Zutritt. Einfach nur schlecht verarbeitet.Kleine Löcher schon enstanden im Fliegengitter und das kleben war… See the full description on the dataset page: https://huggingface.co/datasets/sobamchan/amazon-review-authorship-verification.authorship-attribution-binaryBinary classification dataset for authorship attribution. Each row contains two sets of messages, each set containing at least 250 characters, and a label indicating if the two sets of messages were written by the same author or by two different authors. Three sources are used: reddit comments, discord messages, and blog posts from the Blog Authorship Corpus (license unknown).
Discord messages: 291,648 pairs
Reddit comments: 190,308 pairs
Blog Authorship Corpus: 121,350 pairs
Train set: 573… See the full description on the dataset page: https://huggingface.co/datasets/trentmkelly/authorship-attribution-binary.AuthorMix_AuthorshipObfuscation