Triple
T19033
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oppenheimer–Snyder model |
E376
|
entity |
| Predicate | assumes |
P1458
|
FINISHED |
| Object | spherical symmetry |
—
|
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: spherical symmetry | Statement: [Oppenheimer–Snyder model, assumes, spherical symmetry]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: assumes Context triple: [Oppenheimer–Snyder model, assumes, spherical symmetry]
-
A.
allows
Indicates that one entity grants permission, capability, or opportunity for another entity to perform an action or be in a certain state.
-
B.
approves
Indicates that one entity formally accepts, authorizes, or agrees to a proposal, action, or decision made by another entity.
-
C.
anticipates
Indicates that one entity expects or predicts a future event, action, or state involving another entity before it actually occurs.
-
D.
advises
Indicates that one entity provides guidance, recommendations, or counsel to another entity.
-
E.
proposes
Indicates that one entity formally suggests or puts forward an idea, plan, or course of action to another entity for consideration or approval.
- 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_69a240778d288190815c0052ebbbcc91 |
completed | Feb. 28, 2026, 1:10 a.m. |
| NER | Named-entity recognition | batch_69a246cbca108190a92478df126d9bf8 |
completed | Feb. 28, 2026, 1:37 a.m. |
| PD | Predicate disambiguation | batch_69a2464f61648190ac690044be194972 |
completed | Feb. 28, 2026, 1:35 a.m. |
| PDg | Predicate description generation | batch_69a246cb2904819085c13207565a1db2 |
completed | Feb. 28, 2026, 1:37 a.m. |
Created at: Feb. 28, 2026, 1:14 a.m.