Triple
T18605150
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Macchina di Santa Rosa procession |
E454723
|
entity |
| Predicate | heightOfStructure |
P44247
|
FINISHED |
| Object | about 30 metres |
—
|
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: about 30 metres | Statement: [Macchina di Santa Rosa procession, heightOfStructure, about 30 metres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: heightOfStructure Context triple: [Macchina di Santa Rosa procession, heightOfStructure, about 30 metres]
-
A.
structureHeight
chosen
Indicates that a structure has a specific vertical measurement or height.
-
B.
heightAboveGround
Indicates the vertical distance of an entity measured from the ground surface directly beneath it.
-
C.
heightAboveSurroundings
Indicates that an entity’s vertical position or elevation is higher than that of its immediate surrounding area.
-
D.
roofHeight
Indicates the vertical distance or elevation of a roof relative to a reference level or structure.
-
E.
architecturalHeight
Indicates the measured vertical extent of a structure based on its architectural design, typically from the lowest significant level to the highest architecturally integral point, excluding non-architectural elements like antennas or masts.
- 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_69d8d38bbe7c8190bdec3138e7d413c9 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e547535b8c8190ab5a8a92f15f2bcb |
completed | April 19, 2026, 9:21 p.m. |
| PD | Predicate disambiguation | batch_69e478cf5e888190a0b1074b0c6525df |
completed | April 19, 2026, 6:40 a.m. |
Created at: April 10, 2026, 11:45 a.m.