Triple
T25073709
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Euler class |
E627991
|
entity |
| Predicate | mod2ReductionIs |
P157614
|
FINISHED |
| Object | top Stiefel–Whitney class |
—
|
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: top Stiefel–Whitney class | Statement: [Euler class, mod2ReductionIs, top Stiefel–Whitney class]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mod2ReductionIs Context triple: [Euler class, mod2ReductionIs, top Stiefel–Whitney class]
-
A.
secondCongruenceModulus
Indicates that the second argument specifies the modulus with respect to which two values are congruent in a modular arithmetic relationship.
-
B.
firstCongruenceModulus
Indicates that the specified value is the modulus used in the first congruence of a system of modular equations or congruence relations.
-
C.
thirdCongruenceModulus
Indicates that the third argument serves as the modulus with respect to which two other quantities are congruent.
-
D.
isReductive
Indicates that one entity oversimplifies, diminishes, or reduces the complexity or nuance of another entity, concept, or situation.
-
E.
modulusType
Indicates the type or category of modulus associated with an entity or operation (e.g., which modulus definition or scheme is being used).
- F. None of above. chosen
Provenance (4 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_69e2ff2d71dc8190b4758e57d643cbe4 |
completed | April 18, 2026, 3:49 a.m. |
| NER | Named-entity recognition | batch_69f45d177c3881909ac5058e3e866d93 |
completed | May 1, 2026, 7:58 a.m. |
| PD | Predicate disambiguation | batch_69f442c861188190967655c6d8012380 |
completed | May 1, 2026, 6:06 a.m. |
| PDg | Predicate description generation | batch_69f448fe11f08190bdd53ca7ba2d51e4 |
completed | May 1, 2026, 6:32 a.m. |
Created at: April 18, 2026, 6:20 a.m.