Triple
T23858094
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | La Stupenda |
E592365
|
entity |
| Predicate | associatedWithFame |
P117814
|
FINISHED |
| Object | international opera stages |
—
|
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: international opera stages | Statement: [La Stupenda, associatedWithFame, international opera stages]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWithFame Context triple: [La Stupenda, associatedWithFame, international opera stages]
-
A.
associatedWithFameAspect
Indicates that an entity is connected to or characterized by a particular aspect or dimension of fame.
-
B.
fameFor
Indicates that one entity is widely known or recognized specifically because of, or in connection with, another entity.
-
C.
starMadeFamous
Indicates that one entity (such as a work, event, or role) is what caused another entity (typically a person) to become widely known or famous.
-
D.
famousAt
chosen
Indicates that an entity is widely known or recognized in a particular place, context, or time.
-
E.
wasProminentIn
Indicates that an entity was notably active, influential, or widely recognized within a particular field, context, or time period.
- 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_69e25d22eb488190914b193aff952e83 |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1c98cad34819080baeb8f20f39741 |
completed | April 29, 2026, 9:04 a.m. |
| PD | Predicate disambiguation | batch_69f1614612b481908c45d99e588882f9 |
completed | April 29, 2026, 1:39 a.m. |
Created at: April 17, 2026, 8:12 p.m.