From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-11.)
Dataset Loading has 14 facts recorded in Dontopedia across 3 references, with 5 live disagreements.
Mostly:rdf:type(3), produces(3), rdfs:label(2)
producesusesdescribesreadsFilepartOfOther subjects in dontopedia point AT this entity as a value. These are inverse relationships — e.g. “X motherOf this subject” — and answer questions the forward facts can't. Grouped by predicate.
containsContains(1)ex:code_sectiondescribesDescribes(1)explanation_point_2inputToInput to(1)ex:initial_datasetusedByUsed by(1)ex:readerTimeline axis is valid_time — when each source says the fact was true in the world, not when Dontopedia learned about it. Retracted rows are kept for provenance; coloured stripes indicate the context kind.
doc:beam/6c3b0310-9572-42f3-a33f-3f41bc304470logging_steps=10, evaluation_strategy='epoch', save_total_limit=2, ) # Define the trainer trainer = Trainer( model=model, args=training_args, train_dataset=dataset['train'], eval_dataset=dataset['test'], dat…
doc:beam/c1ca0898-d814-4ebd-a786-a3e5f69b8141# Simulate collecting new feedback new_ratings = [ {'user_id': 1, 'item_id': 10, 'rating': 4}, {'user_id': 2, 'item_id': 11, 'rating': 3}, # Add more new ratings as needed ] return new_ratings # Coll…
doc:beam/77873915-3656-4efe-bfce-aecac2835fe7- **Example**: Check if the reformulated text matches the expected output. ```python class Validator: def __call__(self, text, ground_truth): try: # Check if the reformulated text matches the ground truth …
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