Triple
T698703
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Caméra d’Or |
E13949
|
entity |
| Predicate | festivalSectionInclusion |
P9823
|
FINISHED |
| Object | Official Selection – Competition |
—
|
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: Official Selection – Competition | Statement: [Caméra d’Or, festivalSectionInclusion, Official Selection – Competition]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: festivalSectionInclusion Context triple: [Caméra d’Or, festivalSectionInclusion, Official Selection – Competition]
-
A.
hasFestival
Indicates that a location, community, or entity hosts or holds a festival or celebratory event.
-
B.
peerFestival
Indicates that two festivals are considered peers, sharing a comparable status, scale, or role within a given context.
-
C.
hasCulturalEvent
Indicates that a cultural event (such as a festival, performance, or exhibition) takes place in, is associated with, or is hosted by a given entity.
-
D.
featuresEvent
Indicates that an entity includes, presents, or highlights a particular event as part of its content or offering.
-
E.
partOfEvent
chosen
Indicates that one entity is a component, segment, or sub-activity that belongs to or occurs within a larger event.
- 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_69a493406c408190957eeec9048a8fb6 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a0dd4afc81909e4e869356006f33 |
completed | March 1, 2026, 8:26 p.m. |
| PD | Predicate disambiguation | batch_69a49d2586b081908e052cc5ba1d2685 |
completed | March 1, 2026, 8:10 p.m. |
Created at: March 1, 2026, 7:36 p.m.