Triple
T37510145
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New York World's Fair Corporation |
E932194
|
entity |
| Predicate | organizedEventBorough |
P194591
|
FINISHED |
| Object | Queens |
—
|
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: Queens | Statement: [New York World's Fair Corporation, organizedEventBorough, Queens]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: organizedEventBorough Context triple: [New York World's Fair Corporation, organizedEventBorough, Queens]
-
A.
associatedCityEvent
Indicates a relationship where a city is linked to, involved in, or serves as the location for a particular event.
-
B.
organisedEvent
Indicates that an entity planned, coordinated, and carried out an event.
-
C.
hostedEventsNearby
Indicates that an entity has organized or is responsible for events occurring within a nearby geographic area relative to another reference point.
-
D.
eventTypeOrganized
Indicates that an entity organized or arranged a specific type or category of event.
-
E.
mainEventCity
Indicates the city in which the primary or main event takes place.
- 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_69f76ec5268481909ea01c73aeeefd42 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fd7b0503a08190ba07338365b6fcc9 |
completed | May 8, 2026, 5:56 a.m. |
| PD | Predicate disambiguation | batch_69fd7a9733dc81909199f453c0cc2bc1 |
completed | May 8, 2026, 5:54 a.m. |
| PDg | Predicate description generation | batch_69fd7b042a548190b3abe31bc3258278 |
completed | May 8, 2026, 5:56 a.m. |
Created at: May 3, 2026, 4:17 p.m.