Triple
T25130786
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | R∞ |
E629516
|
entity |
| Predicate | hasPhysicalQuantityType |
P158189
|
FINISHED |
| Object | wavenumber |
—
|
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: wavenumber | Statement: [R∞, hasPhysicalQuantityType, wavenumber]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPhysicalQuantityType Context triple: [R∞, hasPhysicalQuantityType, wavenumber]
-
A.
belongsToPhysicalQuantity
Indicates that one entity is a component, attribute, or part of a specific physical quantity, linking it to that quantity as its owner or container.
-
B.
isScalarQuantity
Indicates that the related physical quantity has only magnitude and no directional component.
-
C.
hasPhysicalLocationType
Indicates that an entity is associated with a specific kind or category of physical location (e.g., building type, facility type, or place type).
-
D.
hasThermodynamicQuantity
Indicates that one entity is associated with, or characterized by, a specific thermodynamic quantity (such as temperature, pressure, or entropy).
-
E.
hasPhysicalNature
Indicates that one entity possesses or exhibits a specific physical form, composition, or material nature in relation to another.
- 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_69e2ff338250819096ff6c8892804389 |
completed | April 18, 2026, 3:49 a.m. |
| NER | Named-entity recognition | batch_69f465f79bd081909a2f5165aa89dc16 |
completed | May 1, 2026, 8:36 a.m. |
| PD | Predicate disambiguation | batch_69f45cfb53f4819099bba48c5057e787 |
completed | May 1, 2026, 7:57 a.m. |
| PDg | Predicate description generation | batch_69f464ae42e88190b3549fdf4e0b425e |
completed | May 1, 2026, 8:30 a.m. |
Created at: April 18, 2026, 6:28 a.m.