Triple
T13605225
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Musée du Temps |
E325042
|
entity |
| Predicate | locatedInBuildingFloorCount |
P110380
|
FINISHED |
| Object | multiple floors |
—
|
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: multiple floors | Statement: [Musée du Temps, locatedInBuildingFloorCount, multiple floors]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: locatedInBuildingFloorCount Context triple: [Musée du Temps, locatedInBuildingFloorCount, multiple floors]
-
A.
numberOfFloors
Indicates the total count of distinct floor levels that a building or structure has.
-
B.
floorCount
Indicates the number of floors or levels that a building or structure has.
-
C.
hasOfficeFloors
Indicates that one entity (typically a building or structure) contains floors that are designated or used as office space.
-
D.
hasFloorsAboveGround
Indicates that an entity (typically a building or structure) possesses a specified number of floors that are located above ground level.
-
E.
floorCountApproximate
Indicates an approximate or estimated number of floors associated with a building or structure.
- 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_69d80769eaf081909d82f44e484d6113 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbbb9ee3f081909056dc1a92c40b7a |
completed | April 12, 2026, 3:34 p.m. |
| PD | Predicate disambiguation | batch_69dbae1b3ee481909bd43ded6227a3e5 |
completed | April 12, 2026, 2:37 p.m. |
| PDg | Predicate description generation | batch_69dbbb8c77dc8190b7bd803b5e168d23 |
completed | April 12, 2026, 3:34 p.m. |
Created at: April 9, 2026, 9:50 p.m.