Triple
T37510144
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New York World's Fair Corporation |
E932194
|
entity |
| Predicate | organizedEventCity |
P80637
|
FINISHED |
| Object | New York City |
—
|
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: New York City | Statement: [New York World's Fair Corporation, organizedEventCity, New York City]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: organizedEventCity Context triple: [New York World's Fair Corporation, organizedEventCity, New York City]
-
A.
associatedCityEvent
Indicates a relationship where a city is linked to, involved in, or serves as the location for a particular event.
-
B.
mainEventCity
chosen
Indicates the city in which the primary or main event takes place.
-
C.
organisedEvent
Indicates that an entity planned, coordinated, and carried out an event.
-
D.
eventManagement
Indicates the organization, coordination, and oversight of all activities and resources involved in planning and executing an event.
-
E.
eventTypeOrganized
Indicates that an entity organized or arranged a specific type or category of 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_69f76ec5268481909ea01c73aeeefd42 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fd783fed9c81909e792702636c4f1f |
completed | May 8, 2026, 5:44 a.m. |
| PD | Predicate disambiguation | batch_69fd7788e63c81909de22fdafcfe41c0 |
completed | May 8, 2026, 5:41 a.m. |
Created at: May 3, 2026, 4:17 p.m.