Triple
T7338224
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Co1 |
E169183
|
entity |
| Predicate | orderFactorization |
P27191
|
FINISHED |
| Object | 2^21 |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: 2^21 | Statement: [Co1, orderFactorization, 2^21]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: orderFactorization Context triple: [Co1, orderFactorization, 2^21]
-
A.
primeFactorization
chosen
Indicates that one entity is the decomposition of another entity into a multiset or sequence of prime factors whose product equals the original.
-
B.
bitLengthFactorization
Indicates a relationship where the bit-length of a number is determined or constrained by the factorization of that number.
-
C.
hasPrimeDecomposition
Indicates that an entity is associated with the factorization of a number into its constituent prime factors.
-
D.
agreesWithFactorialOn
Indicates that a function or expression produces the same values as the factorial function for all inputs in a specified domain.
-
E.
yieldsDecomposition
Indicates that one entity produces or results in a particular breakdown or decomposition of another entity.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69c68a57710481909f0c1f3c6ebdb6f2 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f347f25081908e6086d4073295f5 |
completed | March 27, 2026, 9:14 p.m. |
| PD | Predicate disambiguation | batch_69c6f028fd748190b2ea5c3081958a42 |
completed | March 27, 2026, 9:01 p.m. |
Created at: March 27, 2026, 3:04 p.m.