Triple
T6618282
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wheaton, Maryland |
E149610
|
entity |
| Predicate | escalatorLengthClaim |
P71546
|
FINISHED |
| Object | one of the longest escalators in the Western Hemisphere |
—
|
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: one of the longest escalators in the Western Hemisphere | Statement: [Wheaton, Maryland, escalatorLengthClaim, one of the longest escalators in the Western Hemisphere]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: escalatorLengthClaim Context triple: [Wheaton, Maryland, escalatorLengthClaim, one of the longest escalators in the Western Hemisphere]
-
A.
hasEscalators
Indicates that one entity is equipped with or contains escalators that can be used for movement between different levels or areas.
-
B.
hasElevators
Indicates that one entity is equipped with or contains one or more elevators for vertical transportation.
-
C.
heightClaim
Indicates that one entity asserts or reports a specific height for another entity (or itself).
-
D.
hasSpiralRampLength
Indicates the length measurement of a spiral-shaped ramp in the relationship.
-
E.
elevatorTopSpeed_m_per_s
Indicates the maximum speed, in meters per second, that an elevator can travel.
- 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_69c687ed8a9c81908bb671717cb192ef |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6bdb88cc881908f35648c15a7dc85 |
completed | March 27, 2026, 5:26 p.m. |
| PD | Predicate disambiguation | batch_69c6ad007c1c8190af425f51011c7ad1 |
completed | March 27, 2026, 4:14 p.m. |
| PDg | Predicate description generation | batch_69c6bdb76ec48190b59d576170970cc9 |
completed | March 27, 2026, 5:26 p.m. |
Created at: March 27, 2026, 1:58 p.m.