Triple
T4787816
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 405 Lexington Avenue |
E106525
|
entity |
| Predicate | formerTallestBuildingInWorld |
P1731
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [405 Lexington Avenue, formerTallestBuildingInWorld, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: formerTallestBuildingInWorld Context triple: [405 Lexington Avenue, formerTallestBuildingInWorld, true]
-
A.
formerTallestBuildingInTheWorld
chosen
Indicates that a building once held, but no longer holds, the record for being the tallest building in the world.
-
B.
formerTallestBuildingIn
Indicates that a building was once the tallest building within a specified place or region, but no longer holds that status.
-
C.
formerTallestFreeStandingStructureOnLand
Indicates that one entity was, at some time in the past, the tallest free-standing structure on land relative to the other entity or to all comparable structures.
-
D.
tallestBuildingIn
Indicates that one entity is the tallest building located within the area or region specified by the other entity.
-
E.
wasTallestBuildingInNewYorkUntil
Indicates that a building held the status of being the tallest building in New York up to a specified point in time.
- 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_69bd43f4a9588190bf73e20bc27c03cc |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd65da229c81909c703393f7b9b71d |
completed | March 20, 2026, 3:20 p.m. |
| PD | Predicate disambiguation | batch_69bd622e1b408190806c15c61519fc74 |
completed | March 20, 2026, 3:05 p.m. |
Created at: March 20, 2026, 1:22 p.m.