Input Preprocessing
From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-11.)
Input Preprocessing has 2 facts recorded in Dontopedia across 2 references.
2 facts·2 predicates·2 sources
Maturity scale
raw canonical shape-checked rule-derived certifiedOther facts (2)
The long tail: predicates that appear too rarely to warrant their own section. Filter or scroll to find a specific one. Each row links to its source.
2 facts
| Predicate | Value | Ref |
|---|---|---|
| Ensures | Correct Dtype | [1] |
| Adds | task-prefix | [2] |
Timeline
Timeline 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.
—
ensuresbeam/fa097ab4-7c54-4d7c-bce6-50883cbc7667
ex:correct-dtype
—
addsbeam/eb869acc-2b0a-4006-98fb-a7f182c6bf42
task-prefix
References (2)
2 references
ctx:claims/beam/fa097ab4-7c54-4d7c-bce6-50883cbc7667ctx:claims/beam/eb869acc-2b0a-4006-98fb-a7f182c6bf42- full textbeam-chunktext/plain1 KB
doc:beam/eb869acc-2b0a-4006-98fb-a7f182c6bf42Show excerpt
reformulated_queries = [model.generate(tokenizer(f"reformulate: {q}", return_tensors="pt", max_length=512, truncation=True)['input_ids'], max_length=512)[0] for q in original_queries] reformulated_texts = [tokenizer.decode(output, skip_spec…
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