Triple
T142880
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | George Washington Bridge |
E2889
|
entity |
| Predicate | clearanceBelow |
P6814
|
FINISHED |
| Object | 61 m |
—
|
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: 61 m | Statement: [George Washington Bridge, clearanceBelow, 61 m]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: clearanceBelow Context triple: [George Washington Bridge, clearanceBelow, 61 m]
-
A.
hasClearanceBelow
Indicates that one entity’s clearance level is lower than another entity’s clearance level.
-
B.
lowestPoint
Indicates that one entity is the point with the minimum vertical position or value relative to another entity or within a specified context.
-
C.
numberOfBasementLevels
Indicates the total count of basement levels associated with a given structure or property.
-
D.
hasMezzanine
Indicates that one entity includes or is equipped with a mezzanine level in relation to another entity.
-
E.
hasBasement
Indicates that a building or structure includes a basement level as part of its physical layout.
- 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_69a2521e35c08190b28e5c9f1e3c9b59 |
completed | Feb. 28, 2026, 2:25 a.m. |
| NER | Named-entity recognition | batch_69a2580ca15481909fa3e87d804a1b23 |
completed | Feb. 28, 2026, 2:50 a.m. |
| PD | Predicate disambiguation | batch_69a2565559ac81909e0c4e095a7dfa27 |
completed | Feb. 28, 2026, 2:43 a.m. |
| PDg | Predicate description generation | batch_69a2580b00988190868ee24c0289cf70 |
completed | Feb. 28, 2026, 2:50 a.m. |
Created at: Feb. 28, 2026, 2:31 a.m.