Triple
T3562233
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Plaza Mayor de Valladolid |
E75363
|
entity |
| Predicate | floorCountOfSurroundingBuildings |
P50381
|
FINISHED |
| Object | 3–4 stories |
—
|
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: 3–4 stories | Statement: [Plaza Mayor de Valladolid, floorCountOfSurroundingBuildings, 3–4 stories]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: floorCountOfSurroundingBuildings Context triple: [Plaza Mayor de Valladolid, floorCountOfSurroundingBuildings, 3–4 stories]
-
A.
floorCount
Indicates the number of floors or levels that a building or structure has.
-
B.
numberOfFloors
Indicates the total count of distinct floor levels that a building or structure has.
-
C.
numberOfBuildings
Indicates the total count of buildings associated with a given entity or within a specified context.
-
D.
buildingHeight
Indicates the vertical extent or height measurement of a building.
-
E.
buildingHeightContext
Indicates the contextual or situational factors under which a building’s height is defined, measured, or interpreted.
- 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_69ad85d45090819086f34fb85d850a1e |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc08bdde88190915d2f6ddf26e00e |
completed | March 8, 2026, 6:31 p.m. |
| PD | Predicate disambiguation | batch_69adb834779081908468e182d5f6cf02 |
completed | March 8, 2026, 5:56 p.m. |
| PDg | Predicate description generation | batch_69adb9bbb62c8190989629ca11733e1b |
completed | March 8, 2026, 6:02 p.m. |
Created at: March 8, 2026, 3:21 p.m.