Triple
T24286092
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Documentary section of Busan International Film Festival |
E605672
|
entity |
| Predicate | eventRecurrence |
P112554
|
FINISHED |
| Object | annual |
—
|
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: annual | Statement: [Documentary section of Busan International Film Festival, eventRecurrence, annual]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: eventRecurrence Context triple: [Documentary section of Busan International Film Festival, eventRecurrence, annual]
-
A.
recurringEvent
Indicates that an event occurs repeatedly over time according to some regular pattern or schedule.
-
B.
recurrenceType
chosen
Indicates the pattern or frequency with which an event or action repeats over time.
-
C.
recurringSeries
Indicates that an event, action, or pattern occurs repeatedly over time as part of an ongoing series rather than as a one-time instance.
-
D.
recurringDuring
Indicates that an event or state happens repeatedly within the time span or context defined by another event or interval.
-
E.
recurringLocation
Indicates that an event, action, or state happens repeatedly at the specified location over time.
- 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_69e295480d0c8190846fc3c2e2da1d4c |
completed | April 17, 2026, 8:17 p.m. |
| NER | Named-entity recognition | batch_69f28f5605f081908367bd08ab1ec9ab |
completed | April 29, 2026, 11:08 p.m. |
| PD | Predicate disambiguation | batch_69f1c457a2908190993824395b3c365d |
completed | April 29, 2026, 8:41 a.m. |
Created at: April 18, 2026, 12:08 a.m.