Triple
T28960026
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ultra Korea |
E731869
|
entity |
| Predicate | relatedFestivalSeries |
P202662
|
FINISHED |
| Object | Ultra Worldwide |
—
|
NE NERFINISHED |
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: Ultra Worldwide | Statement: [Ultra Korea, relatedFestivalSeries, Ultra Worldwide]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relatedFestivalSeries Context triple: [Ultra Korea, relatedFestivalSeries, Ultra Worldwide]
-
A.
relatedFestivalType
Indicates that one festival is associated with another through a shared or corresponding festival type or category.
-
B.
relatedFestivalDate
Indicates that there is a specific calendar date associated with a particular festival or celebration.
-
C.
associatedFestivalOrCustom
Indicates a festival or custom that is traditionally linked or related to the given entity.
-
D.
linkedFestival
Indicates that two entities are associated through a common festival, event, or celebration.
-
E.
linksFestivalTo
Indicates that one entity is associated with, connected to, or participates in a particular festival.
- F. None of above. chosen
Provenance (4 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_69f043ee242c8190b063248b417c5a69 |
completed | April 28, 2026, 5:21 a.m. |
| NER | Named-entity recognition | batch_6a00a846a8f881908b073ad13a5af6ca |
completed | May 10, 2026, 3:46 p.m. |
| PD | Predicate disambiguation | batch_6a00a7aae194819085e1a2fd406f7922 |
completed | May 10, 2026, 3:43 p.m. |
| PDg | Predicate description generation | batch_6a00a845f574819085e80f0fd573a74f |
completed | May 10, 2026, 3:46 p.m. |
Created at: April 28, 2026, 8:49 a.m.