Triple
T8101798
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 151 West 42nd Street |
E189130
|
entity |
| Predicate | hasOfficeFloors |
P80467
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [151 West 42nd Street, hasOfficeFloors, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOfficeFloors Context triple: [151 West 42nd Street, hasOfficeFloors, yes]
-
A.
numberOfFloors
Indicates the total count of distinct floor levels that a building or structure has.
-
B.
hasFloorsAboveGround
Indicates that an entity (typically a building or structure) possesses a specified number of floors that are located above ground level.
-
C.
numberOfOffices
Indicates the total count of offices associated with a given entity.
-
D.
hasOfficeBuildings
Indicates that one entity possesses, controls, or is associated with one or more office buildings.
-
E.
numberOfFloorsServed
Indicates the total count of distinct floors that are served or accessed by a given entity (such as an elevator or service system).
- 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_69ca82b886d88190a9cba0d5a4a27521 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb42bbf20c8190aa8c272b5c39002d |
completed | March 31, 2026, 3:42 a.m. |
| PD | Predicate disambiguation | batch_69cb04a14cd88190a79ed26cbeec1c33 |
completed | March 30, 2026, 11:17 p.m. |
| PDg | Predicate description generation | batch_69cb14be17208190bb51c3dfcb613f20 |
completed | March 31, 2026, 12:26 a.m. |
Created at: March 30, 2026, 5:31 p.m.