Triple
T380019
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cooper pair |
E8656
|
entity |
| Predicate | isModeledAs |
P2006
|
FINISHED |
| Object | pairing of time-reversed states |
—
|
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: pairing of time-reversed states | Statement: [Cooper pair, isModeledAs, pairing of time-reversed states]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isModeledAs Context triple: [Cooper pair, isModeledAs, pairing of time-reversed states]
-
A.
model
chosen
Indicates that one entity serves as a representation, example, or simulation of another entity or concept.
-
B.
isUsedAs
Indicates that one entity serves a particular function, role, or purpose as another entity.
-
C.
isBackboneOf
Indicates that one entity forms the main supporting structure or central framework upon which another entity fundamentally depends.
-
D.
isPartOfType
Indicates that one type or category is a constituent or subset within a larger, encompassing type or category.
-
E.
notableModel
Indicates that an entity is a particularly important, influential, or exemplary instance or version within a broader category or system.
- 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_69a2e7f47dd08190a4e294ccbbe46cd4 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ec2b07248190979229bad3a741c9 |
completed | Feb. 28, 2026, 1:22 p.m. |
| PD | Predicate disambiguation | batch_69a2e964d4b481909290e474b0341e3c |
completed | Feb. 28, 2026, 1:11 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.