Triple
T824272
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Trump International Hotel & Tower |
E17818
|
entity |
| Predicate | hasLocationType |
P6822
|
FINISHED |
| Object | major city |
—
|
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: major city | Statement: [Trump International Hotel & Tower, hasLocationType, major city]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLocationType Context triple: [Trump International Hotel & Tower, hasLocationType, major city]
-
A.
hasTypeLocality
Indicates the specific geographic location where an entity (typically a species or specimen) was originally found and formally described.
-
B.
hasRelativeLocation
Indicates that one entity is positioned in space in relation to another entity’s location.
-
C.
hasAreaType
chosen
Indicates that an entity is associated with a specific kind or classification of area (e.g., urban, rural, coastal).
-
D.
hasFacilityType
Indicates that an entity possesses or is associated with a specific type or category of facility.
-
E.
refersToLocation
Indicates that one entity designates, points to, or identifies a specific location associated with it.
- 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_69a4937c9c188190aaa216f6b466f452 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4ab7d3984819089aefbf12d3b3c2c |
completed | March 1, 2026, 9:11 p.m. |
| PD | Predicate disambiguation | batch_69a4aa781e1081909df006f730296c53 |
completed | March 1, 2026, 9:07 p.m. |
Created at: March 1, 2026, 7:38 p.m.