Triple
T210627
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bekenstein–Hawking entropy |
E4708
|
entity |
| Predicate | isGeometric |
P9152
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Bekenstein–Hawking entropy, isGeometric, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isGeometric Context triple: [Bekenstein–Hawking entropy, isGeometric, true]
-
A.
hasGeodesics
Indicates that the subject possesses or is characterized by geodesic paths, typically representing shortest or straightest possible routes within a given space or geometry.
-
B.
isSeriesOf
Indicates that one entity is a sequence or set of related items that collectively form a series associated with another entity.
-
C.
isConcaveIn
Indicates that a function or relation curves inward (is concave) with respect to a specified variable or argument, so that any line segment between two points on its graph lies below or on the graph.
-
D.
isComposite
Indicates that an entity is made up of multiple components or parts combined into a single whole.
-
E.
hasCurvatureInvariant
Indicates that one entity possesses a specific curvature-related invariant property or value associated with its geometric or mathematical structure.
- 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_69a2575cb1dc8190a01ad332426dc339 |
completed | Feb. 28, 2026, 2:47 a.m. |
| NER | Named-entity recognition | batch_69a25d35aa288190966b6e15af1525cb |
completed | Feb. 28, 2026, 3:12 a.m. |
| PD | Predicate disambiguation | batch_69a25b4f71b88190866c8262922ae204 |
completed | Feb. 28, 2026, 3:04 a.m. |
| PDg | Predicate description generation | batch_69a25d3463648190ac716d7475378536 |
completed | Feb. 28, 2026, 3:12 a.m. |
Created at: Feb. 28, 2026, 2:52 a.m.