Triple
T33288616
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Open Flair Festival |
E852252
|
entity |
| Predicate | hasFoodAndBeverageStalls |
P70493
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Open Flair Festival, hasFoodAndBeverageStalls, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFoodAndBeverageStalls Context triple: [Open Flair Festival, hasFoodAndBeverageStalls, yes]
-
A.
hasFoodVendors
Indicates that one entity provides or hosts food vendors that operate at or within another entity.
-
B.
hasStreetFood
Indicates that one entity offers, features, or is associated with street food in relation to another entity.
-
C.
marketStallsCountApprox
Indicates that the number of market stalls associated with an entity is known only approximately rather than as an exact count.
-
D.
alsoEats
Indicates that an entity consumes something in addition to another item or items it already eats.
-
E.
offersFoodAndBeverage
chosen
Indicates that an entity provides both food and drink to another entity or for general consumption.
- 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_69f349660ff48190a4568803d0b89941 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69fd974d75e08190af46b1d608769f3b |
completed | May 8, 2026, 7:57 a.m. |
| PD | Predicate disambiguation | batch_69fd94ff792c8190bedf4a639d3da809 |
completed | May 8, 2026, 7:47 a.m. |
Created at: May 1, 2026, 1:32 a.m.