Triple
T32043793
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Milne universe model |
E818283
|
entity |
| Predicate | hasCurvatureParameter |
P193368
|
FINISHED |
| Object | k = -1 |
—
|
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: k = -1 | Statement: [Milne universe model, hasCurvatureParameter, k = -1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCurvatureParameter Context triple: [Milne universe model, hasCurvatureParameter, k = -1]
-
A.
hasCurvatureBehavior
Indicates how the curvature of an object or path behaves or changes under specified conditions or over a given domain.
-
B.
hasCurvatureInvariant
Indicates that one entity possesses a specific curvature-related invariant property or value associated with its geometric or mathematical structure.
-
C.
hasSpatialCurvature
chosen
Indicates that one entity possesses or exhibits a non-zero curvature in its spatial geometry relative to another frame or reference.
-
D.
hasCurvatureNormalization
Indicates that a curvature value has been adjusted or scaled according to a specified normalization method or standard.
-
E.
usesCurvature
Indicates that one entity applies or relies on the curvature property or measure of another entity in its operation, definition, or analysis.
- 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_69f348fcfb648190859f6be5e04b7cfe |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69fd485f57dc8190820365396d041991 |
completed | May 8, 2026, 2:20 a.m. |
| PD | Predicate disambiguation | batch_69fd47d35da081908bec8901018d186c |
completed | May 8, 2026, 2:17 a.m. |
Created at: May 1, 2026, 12:19 a.m.