Triple
T25828826
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Planck density |
E650603
|
entity |
| Predicate | isUpperScaleFor |
P14327
|
FINISHED |
| Object | classical general relativity applicability |
—
|
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: classical general relativity applicability | Statement: [Planck density, isUpperScaleFor, classical general relativity applicability]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isUpperScaleFor Context triple: [Planck density, isUpperScaleFor, classical general relativity applicability]
-
A.
hasScale
Indicates that one entity possesses or is characterized by a scale or graduated measurement system related to another entity.
-
B.
coversScale
Indicates that one entity spans, includes, or applies across the full range or extent of another entity’s scale.
-
C.
scalesWith
Indicates that a change in one quantity is systematically associated with a proportional or otherwise dependent change in another quantity.
-
D.
hasScales
Indicates that an entity possesses scales as a surface covering or body feature.
-
E.
isUpperBoundFor
chosen
Indicates that one value is greater than or equal to every element in a given set or collection, serving as an upper limit for them.
- 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_69e7ab37438081908f1ccf6284839520 |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f6019807f08190bbeb8be744551fdf |
completed | May 2, 2026, 1:52 p.m. |
| PD | Predicate disambiguation | batch_69f4938b960081909b53c074a3e0c7c2 |
completed | May 1, 2026, 11:50 a.m. |
Created at: April 22, 2026, 7:37 a.m.