Triple
T18437674
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Washington Avenue (Miami Beach) |
E450434
|
entity |
| Predicate | hasBuildingHeights |
P3373
|
FINISHED |
| Object | low- to mid-rise |
—
|
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: low- to mid-rise | Statement: [Washington Avenue (Miami Beach), hasBuildingHeights, low- to mid-rise]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBuildingHeights Context triple: [Washington Avenue (Miami Beach), hasBuildingHeights, low- to mid-rise]
-
A.
hasBuildingHeightType
chosen
Indicates the classification or type used to characterize the height of a building in the relationship.
-
B.
hasHighRiseBuildings
Indicates that the subject location contains one or more tall, multi-story buildings commonly classified as high-rises.
-
C.
buildingHeight
Indicates the vertical extent or height measurement of a building.
-
D.
buildingHeightContext
Indicates the contextual or situational factors under which a building’s height is defined, measured, or interpreted.
-
E.
hasTowerHeight
Indicates that an entity (such as a tower or structure) has a specific height value associated with it.
- 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_69d8d381d6388190a9e94e9c658174e4 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e51c0e04508190bc851a8954ae60e8 |
completed | April 19, 2026, 6:16 p.m. |
| PD | Predicate disambiguation | batch_69e469c943a4819094c8fdc5971ad3a7 |
completed | April 19, 2026, 5:36 a.m. |
Created at: April 10, 2026, 11:29 a.m.