Triple
T4787812
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 405 Lexington Avenue |
E106525
|
entity |
| Predicate | numberOfFloorsOfAssociatedBuilding |
P1514
|
FINISHED |
| Object | 77 |
—
|
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: 77 | Statement: [405 Lexington Avenue, numberOfFloorsOfAssociatedBuilding, 77]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfFloorsOfAssociatedBuilding Context triple: [405 Lexington Avenue, numberOfFloorsOfAssociatedBuilding, 77]
-
A.
numberOfFloors
Indicates the total count of distinct floor levels that a building or structure has.
-
B.
numberOfResidentialFloors
Indicates the total count of floors in a building that are designated for residential use.
-
C.
floorCountOfSurroundingBuildings
Indicates the number of floors in the buildings that are located around or near a given reference building or area.
-
D.
numberOfFloorsServed
Indicates the total count of distinct floors that are served or accessed by a given entity (such as an elevator or service system).
-
E.
floorCount
chosen
Indicates the number of floors or levels that a building or structure has.
- 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.