Triple
T37607459
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 430 Park Avenue |
E935692
|
entity |
| Predicate | hasRestroomsOnMultipleFloors |
P206002
|
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: [430 Park Avenue, hasRestroomsOnMultipleFloors, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRestroomsOnMultipleFloors Context triple: [430 Park Avenue, hasRestroomsOnMultipleFloors, true]
-
A.
hasRestrooms
Indicates that a place or facility provides access to restroom or toilet amenities.
-
B.
hasMultipleFloors
Indicates that an entity consists of more than one distinct floor or level within a structure.
-
C.
hasRestaurantFloors
Indicates that a restaurant occupies or is distributed across a specified number of floors in a building.
-
D.
locatedInBuildingFloorCount
Indicates that one entity is located in or associated with a building characterized by a specific number of floors.
-
E.
numberOfFloors
Indicates the total count of distinct floor levels that a building or structure has.
- 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_69f76ed0a85481909254a8a89090c826 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_6a037cad051c8190b28b354b89208574 |
completed | May 12, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_6a037a1553e08190bb7424c448cb1f33 |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c842b2c819082f1d2db995ac2eb |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 3, 2026, 4:18 p.m.