Triple
T22550181
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Georgi–Glashow model |
E557536
|
entity |
| Predicate | typeOfUnification |
P62057
|
FINISHED |
| Object | gauge unification |
—
|
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: gauge unification | Statement: [Georgi–Glashow model, typeOfUnification, gauge unification]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfUnification Context triple: [Georgi–Glashow model, typeOfUnification, gauge unification]
-
A.
unificationType
chosen
Indicates the specific manner or category in which two or more entities are combined, merged, or treated as a single unified whole.
-
B.
typeOfUnion
Indicates the specific kind or category of union relationship that exists between the related entities.
-
C.
typeOfCanonization
Indicates the specific form or category of canonization by which an entity was officially declared sacred or recognized as a saint.
-
D.
unificationPrinciple
Indicates that multiple entities, concepts, or elements are brought together into a single, coherent whole according to a common principle or framework.
-
E.
unificationPossible
Indicates that two entities can be combined or reconciled into a single, consistent representation under a shared set of constraints or rules.
- 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_69e11e59db848190b4272ecd2b690ffd |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15f7546c4819099942c86ca522a60 |
completed | April 29, 2026, 1:31 a.m. |
| PD | Predicate disambiguation | batch_69e898cb3fb48190add6ab24a2df5822 |
completed | April 22, 2026, 9:45 a.m. |
Created at: April 16, 2026, 8:52 p.m.