Triple
T210650
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kretschmann scalar |
E4709
|
entity |
| Predicate | behaviorNear |
P9154
|
FINISHED |
| Object | r = 0 in Schwarzschild spacetime diverges to infinity |
—
|
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: r = 0 in Schwarzschild spacetime diverges to infinity | Statement: [Kretschmann scalar, behaviorNear, r = 0 in Schwarzschild spacetime diverges to infinity]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: behaviorNear Context triple: [Kretschmann scalar, behaviorNear, r = 0 in Schwarzschild spacetime diverges to infinity]
-
A.
near
Indicates that one entity is located at a short distance from another entity in space or position.
-
B.
neighborhood
Indicates that one entity is located in close spatial proximity to another, typically within the same local area or district.
-
C.
positionB
Indicates that one entity occupies or is located at a specific position relative to another entity.
-
D.
movementType
Indicates the manner or mode in which an entity moves or is moved from one place or state to another.
-
E.
orientation
Indicates the relative directional alignment or facing of one entity with respect to another or to a reference frame.
- 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.