Triple
T30187665
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nit de l'Alba |
E767380
|
entity |
| Predicate | typeOfFireworks |
P45831
|
FINISHED |
| Object | aerial fireworks |
—
|
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: aerial fireworks | Statement: [Nit de l'Alba, typeOfFireworks, aerial fireworks]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfFireworks Context triple: [Nit de l'Alba, typeOfFireworks, aerial fireworks]
-
A.
hasPyrotechnics
chosen
Indicates that an entity includes, uses, or features pyrotechnic effects or fireworks as part of its characteristics or activities.
-
B.
fireworksCompany
Indicates a relationship where an entity is a company that produces, sells, or organizes fireworks displays for another entity or context.
-
C.
explosionType
Indicates the specific kind or category of explosion associated with an event or entity.
-
D.
fireworksLocation
Indicates the place where fireworks are set off, displayed, or occur.
-
E.
typeOfLantern
Indicates that one entity is a specific kind or category of lantern relative to another.
- 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_69f2247cc3d88190811dec3face94bf5 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69ff45793d5c81909dc503ad1f714ee2 |
completed | May 9, 2026, 2:32 p.m. |
| PD | Predicate disambiguation | batch_69ff41cb0e088190a6e9b03cb20e5fad |
completed | May 9, 2026, 2:16 p.m. |
Created at: April 29, 2026, 7:27 p.m.