Triple
T1250537
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hawking radiation |
E26863
|
entity |
| Predicate | modeledAs |
P2006
|
FINISHED |
| Object | particle emission 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: particle emission to infinity | Statement: [Hawking radiation, modeledAs, particle emission to infinity]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: modeledAs Context triple: [Hawking radiation, modeledAs, particle emission to infinity]
-
A.
model
chosen
Indicates that one entity serves as a representation, example, or simulation of another entity or concept.
-
B.
hasModelledFor
Indicates that one entity has served as a model for another entity, typically in a professional or representational context such as art, photography, or fashion.
-
C.
envisionedAs
Indicates that one entity is mentally pictured, imagined, or conceived in terms of another entity or role.
-
D.
notableModel
Indicates that an entity is a particularly important, influential, or exemplary instance or version within a broader category or system.
-
E.
observedAs
Indicates that one entity is perceived, recorded, or identified in the role, state, or form of another entity.
- 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_69a49487a9c48190ba9b05348fd1b53f |
completed | March 1, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69a4bf84c73c8190bbb14265cd7ab6ae |
completed | March 1, 2026, 10:36 p.m. |
| PD | Predicate disambiguation | batch_69a4bb6b075881908e867c25b5080e25 |
completed | March 1, 2026, 10:19 p.m. |
Created at: March 1, 2026, 7:47 p.m.