Triple
T11761889
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New York Marriott Marquis |
E279676
|
entity |
| Predicate | hasElevatorType |
P1531
|
FINISHED |
| Object | express elevators |
—
|
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: express elevators | Statement: [New York Marriott Marquis, hasElevatorType, express elevators]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasElevatorType Context triple: [New York Marriott Marquis, hasElevatorType, express elevators]
-
A.
hasElevators
chosen
Indicates that one entity is equipped with or contains one or more elevators for vertical transportation.
-
B.
hasElevatorConnection
Indicates that there is a direct elevator-based connection or access route between two locations or entities.
-
C.
hasEscalators
Indicates that one entity is equipped with or contains escalators that can be used for movement between different levels or areas.
-
D.
hasHighSpeedElevators
Indicates that a building or structure is equipped with elevators capable of operating at high speeds.
-
E.
hasNumberOfElevatorBanks
Indicates the relationship specifying how many distinct elevator banks are present in or associated with a given entity.
- 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_69d6ab01d2688190ad8ed6bda487eaa5 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a52386708190b744746a2db37495 |
completed | April 10, 2026, 7:22 a.m. |
| PD | Predicate disambiguation | batch_69d88a829fe481909cc5431de7d6058e |
completed | April 10, 2026, 5:28 a.m. |
Created at: April 8, 2026, 9:41 p.m.