Triple
T1286196
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Huang–Rhys factor |
E27438
|
entity |
| Predicate | usedInModel |
P25490
|
FINISHED |
| Object | configuration coordinate model |
—
|
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: configuration coordinate model | Statement: [Huang–Rhys factor, usedInModel, configuration coordinate model]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedInModel Context triple: [Huang–Rhys factor, usedInModel, configuration coordinate model]
-
A.
areUsedIn
chosen
Indicates that certain entities serve as components, tools, or resources within a particular process, context, or application.
-
B.
usedInType
Indicates that something serves as a component, element, or example within a particular type or category.
-
C.
isUsedAs
Indicates that one entity serves a particular function, role, or purpose as another entity.
-
D.
usedInPartOf
Indicates that something is utilized or plays a functional role within a specific component or subpart of a larger whole.
-
E.
usedInProject
Indicates that something (such as a resource, tool, or component) is employed or utilized within a particular project.
- 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_69a496d4ec448190ad653b2590c46711 |
completed | March 1, 2026, 7:43 p.m. |
| NER | Named-entity recognition | batch_69a4c0b85eb48190a8b61dc397fa6390 |
completed | March 1, 2026, 10:42 p.m. |
| PD | Predicate disambiguation | batch_69a4bee276d8819092f71c5a1140bb61 |
completed | March 1, 2026, 10:34 p.m. |
Created at: March 1, 2026, 7:51 p.m.