Triple
T23977372
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kobe City Hall |
E604405
|
entity |
| Predicate | hasFloorSpaceUse |
P154103
|
FINISHED |
| Object | administrative offices |
—
|
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: administrative offices | Statement: [Kobe City Hall, hasFloorSpaceUse, administrative offices]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFloorSpaceUse Context triple: [Kobe City Hall, hasFloorSpaceUse, administrative offices]
-
A.
hasFloorUse
Indicates that a particular floor or level of a building is designated for a specific function, activity, or type of use.
-
B.
hasFloorArea
Indicates that an entity possesses a specified amount of floor space as a measurable area.
-
C.
hasUpperFloorUse
Indicates that an entity’s upper floor is assigned or designated for a particular use or function.
-
D.
hasGroundFloorUse
Indicates that a building or structure is associated with a specific functional use assigned to its ground floor level.
-
E.
hasFloor
Indicates that one entity possesses, includes, or is associated with a particular floor or level within a 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_69e29543f40c819087700b7a272afb60 |
completed | April 17, 2026, 8:17 p.m. |
| NER | Named-entity recognition | batch_69f1d2bad6ec81908b5649223a72c2b9 |
completed | April 29, 2026, 9:43 a.m. |
| PD | Predicate disambiguation | batch_69f161578d54819084a8b35496299993 |
completed | April 29, 2026, 1:39 a.m. |
| PDg | Predicate description generation | batch_69f167dca3608190ace9d2eef56b2af6 |
completed | April 29, 2026, 2:07 a.m. |
Created at: April 17, 2026, 9:26 p.m.