Triple
T19041
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oppenheimer–Snyder model |
E376
|
entity |
| Predicate | matches |
P1460
|
FINISHED |
| Object | interior FLRW solution to exterior Schwarzschild solution |
—
|
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: interior FLRW solution to exterior Schwarzschild solution | Statement: [Oppenheimer–Snyder model, matches, interior FLRW solution to exterior Schwarzschild solution]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: matches Context triple: [Oppenheimer–Snyder model, matches, interior FLRW solution to exterior Schwarzschild solution]
-
A.
meets
Indicates that two or more entities come together at the same place and time, typically for interaction or a shared purpose.
-
B.
meetsAs
Indicates that two entities encounter or come together at the same place and time, typically in a planned or recognized interaction.
-
C.
mentions
Indicates that one entity refers to, cites, or brings up another entity in some form of communication or content.
-
D.
passes
Indicates that one entity successfully transfers, hands over, or moves something (such as an object, message, or responsibility) to another entity.
-
E.
complements
Indicates that one entity enhances, completes, or improves another by providing qualities or functions that fit well together.
- 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.