Triple
T1388251
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Busan Fireworks Festival |
E29894
|
entity |
| Predicate | hasSideEvents |
P6285
|
FINISHED |
| Object | pre-festival cultural programs |
—
|
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: pre-festival cultural programs | Statement: [Busan Fireworks Festival, hasSideEvents, pre-festival cultural programs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSideEvents Context triple: [Busan Fireworks Festival, hasSideEvents, pre-festival cultural programs]
-
A.
hasBside
Indicates that one item serves as the B-side counterpart or secondary track associated with another primary item, typically in a recording or media release.
-
B.
hasEventSpace
Indicates that an entity provides or includes a designated space intended for hosting events.
-
C.
hadEvent
Indicates that an entity experienced, hosted, or was associated with a specific event at some point in time.
-
D.
hasCommonSideEffect
Indicates that two or more treatments, drugs, or interventions share at least one side effect in common.
-
E.
hasSubEvent
chosen
Indicates that an event is composed of, or includes as part of its structure, another event that occurs within it.
- 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_69a498dc92f8819094a1108f8ac90f43 |
completed | March 1, 2026, 7:51 p.m. |
| NER | Named-entity recognition | batch_69a4c35ad578819090abf96222112bda |
completed | March 1, 2026, 10:53 p.m. |
| PD | Predicate disambiguation | batch_69a4beffcf808190ab4cd0271257ce63 |
completed | March 1, 2026, 10:34 p.m. |
Created at: March 1, 2026, 7:59 p.m.