facts
Datasets
All datasets matching “facts”personal-facts-msc
Personal Facts (MSC) — Multi-Dimensional Annotation
A manually annotated dataset of 2,779 personal facts sampled from the
Multi-Session Chat (MSC)
corpus, labeled across seven dimensions that jointly characterize a fact's
topic, temporal anchoring, referent, lifetime, validity, and dialogue-continuation
potential.
The scheme extends PeaCoK with
two new top-level categories (Demographics, Possessions) and three new
dimensions (Duration, Validity / Invalidity Reason, Followup),
and… See the full description on the dataset page: https://huggingface.co/datasets/adugeen/personal-facts-msc.factnet_factsynset
FactSynset Dataset
Overview
FactSynset is the semantic equivalence layer of FactNet that aggregates similar FactStatements into unified semantic classes with normalized values. It provides a cross-lingual view of semantically equivalent facts, enabling reasoning across language barriers.
Paper: https://arxiv.org/abs/2602.03417
Github: https://github.com/yl-shen/factnet
Dataset: https://huggingface.co/collections/openbmb/factnet
Dataset Format
The dataset… See the full description on the dataset page: https://huggingface.co/datasets/openbmb/factnet_factsynset.factnet_factsense
FactSense Dataset
Overview
FactSense is the linguistic layer of FactNet that provides multilingual, natural language expressions of facts extracted from Wikipedia pages. Each FactSense instance represents a FactStatement realized in natural text with provenance information.
Paper: https://arxiv.org/abs/2602.03417
Github: https://github.com/yl-shen/factnet
Dataset: https://huggingface.co/collections/openbmb/factnet
Dataset Format
The dataset contains… See the full description on the dataset page: https://huggingface.co/datasets/openbmb/factnet_factsense.factnet_factstatements
FactStatement Dataset
Overview
FactStatement is the foundational layer of FactNet, a cross-lingual, multi-layered fact knowledge graph. FactStatements are language-neutral, atomic fact units directly mapped from Wikidata statements, forming the core building blocks of the knowledge graph.
Paper: https://arxiv.org/abs/2602.03417
Github: https://github.com/yl-shen/factnet
Dataset: https://huggingface.co/collections/openbmb/factnet
Dataset Format
The dataset… See the full description on the dataset page: https://huggingface.co/datasets/openbmb/factnet_factstatements.FACTS-grounding-public
FACTS Grounding 1.0 Public Examples
860 public FACTS Grounding examples from Google DeepMind and Google Research
FACTS Grounding is a benchmark from Google DeepMind and Google Research designed to measure the performance of AI Models on factuality and grounding.
▶ FACTS Grounding Leaderboard on Kaggle▶ Technical Report▶ Evaluation Starter Code▶ Google DeepMind Blog Post
Usage
The FACTS Grounding benchmark evaluates the ability of Large Language Models (LLMs)… See the full description on the dataset page: https://huggingface.co/datasets/google/FACTS-grounding-public.live-facts-snapshot
Live Facts Snapshot
A daily snapshot of verifiable, post-training-cutoff world-state facts — the kind of
ground truth language models cannot know from training data — exported through
Dynamic Feed, a live, verifiable data API whose every response
is Ed25519-signed. One file per day (data/YYYY-MM-DD.jsonl), one fact per line, and
every row carries its own source, source_url and measured_at.
Facts covered per day:
tool
facts
upstream source
licence
software_version… See the full description on the dataset page: https://huggingface.co/datasets/dynamicfeed/live-facts-snapshot.