Triple
T24065205
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sullivan minimal model |
E596068
|
entity |
| Predicate | hasGeneratorDegrees |
P154721
|
FINISHED |
| Object | positive integers (for simply connected spaces) |
—
|
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: positive integers (for simply connected spaces) | Statement: [Sullivan minimal model, hasGeneratorDegrees, positive integers (for simply connected spaces)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGeneratorDegrees Context triple: [Sullivan minimal model, hasGeneratorDegrees, positive integers (for simply connected spaces)]
-
A.
hasNumberOfDegrees
Indicates the quantity of academic degrees that an entity possesses.
-
B.
hasStandardGenerators
Indicates that an entity possesses a designated or commonly accepted set of generators that define or produce it according to a standard.
-
C.
hasDegreeLength
Indicates that something possesses a length measured in degrees, typically expressing angular extent or size.
-
D.
hasCoreDegrees
Indicates that an entity possesses one or more primary or foundational academic degrees.
-
E.
isDegreeOf
Indicates that one entity is an academic or professional degree held, pursued, or associated with another entity.
- 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_69e288c25c008190850cf447940ab181 |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f1da5aa1a48190afec72bbcfd379c3 |
completed | April 29, 2026, 10:15 a.m. |
| PD | Predicate disambiguation | batch_69f1764b1d4c8190b12590c6339c31c1 |
completed | April 29, 2026, 3:08 a.m. |
| PDg | Predicate description generation | batch_69f1785afe3c81909be28986ffe944bf |
completed | April 29, 2026, 3:17 a.m. |
Created at: April 17, 2026, 10:39 p.m.