Triple
T12481545
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Carreras |
E298318
|
entity |
| Predicate | associatedWithCulturalDomain |
P81632
|
FINISHED |
| Object | opera |
—
|
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: opera | Statement: [Carreras, associatedWithCulturalDomain, opera]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWithCulturalDomain Context triple: [Carreras, associatedWithCulturalDomain, opera]
-
A.
hasAssociatedCulture
Indicates that an entity is related to, influenced by, or characterized by a particular culture.
-
B.
hasCulturalScope
Indicates that a relationship or action is limited to, relevant within, or characterized by a particular cultural context or domain.
-
C.
hasCulturalSignificanceFor
Indicates that something holds particular cultural meaning, value, or importance for a specified group or community.
-
D.
hasCulturalConcept
Indicates that an entity embodies, includes, or is associated with a particular cultural idea, value, practice, or construct.
-
E.
culturalType
chosen
Indicates the classification of something according to its cultural category, style, or tradition.
- 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_69d6ada377208190a36011199a4d8558 |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d94e8a706c8190873623eab7db607d |
completed | April 10, 2026, 7:24 p.m. |
| PD | Predicate disambiguation | batch_69d94d41f3cc8190a3331fb9a895306f |
completed | April 10, 2026, 7:19 p.m. |
Created at: April 8, 2026, 9:56 p.m.