Triple
T3484852
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Adelaide Fringe |
E73581
|
entity |
| Predicate | venueModel |
P8643
|
FINISHED |
| Object | uses both traditional and pop-up venues |
—
|
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: uses both traditional and pop-up venues | Statement: [Adelaide Fringe, venueModel, uses both traditional and pop-up venues]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: venueModel Context triple: [Adelaide Fringe, venueModel, uses both traditional and pop-up venues]
-
A.
venueOperator
Indicates that one entity operates, manages, or runs a particular venue or event location for another entity.
-
B.
venueConcept
chosen
Indicates a relationship where a venue is associated with, characterized by, or defined in terms of a particular concept or thematic idea.
-
C.
venue
Indicates the place or location where an event, activity, or interaction takes place.
-
D.
venueSelection
Indicates the relationship in which a specific venue is chosen or designated for an event, activity, or purpose among available options.
-
E.
venueComplex
Indicates that one venue is a complex or larger facility that contains or encompasses another venue.
- 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_69ad85b3c9b08190857cae74c7f36da9 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adbb795db88190805b26d9774fdb73 |
completed | March 8, 2026, 6:10 p.m. |
| PD | Predicate disambiguation | batch_69adae0935ac8190bfa8a8bd3dcd3301 |
completed | March 8, 2026, 5:12 p.m. |
Created at: March 8, 2026, 3:17 p.m.