Triple
T25718303
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | National Library of Korea |
E644916
|
entity |
| Predicate | mainBuildingFloorsBelowGround |
P996
|
FINISHED |
| Object | 2 |
—
|
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: 2 | Statement: [National Library of Korea, mainBuildingFloorsBelowGround, 2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainBuildingFloorsBelowGround Context triple: [National Library of Korea, mainBuildingFloorsBelowGround, 2]
-
A.
hasUndergroundLevel
Indicates that one entity possesses or includes a level, floor, or section that is located below ground level.
-
B.
hasFloorsAboveGround
Indicates that an entity (typically a building or structure) possesses a specified number of floors that are located above ground level.
-
C.
numberOfBasementLevels
chosen
Indicates the total count of basement levels associated with a given structure or property.
-
D.
hasBaseBuildingFloors
Indicates that something (such as a building or structure) has a specified number of floors in its base or main part.
-
E.
floorCountIncludingBasement
Indicates the total number of floors in a building, counting all above-ground levels plus any basement levels.
- 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_69e77e8476fc8190bd5e9d05b89fad0a |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f5fc64597c8190bfd867fb93834195 |
completed | May 2, 2026, 1:30 p.m. |
| PD | Predicate disambiguation | batch_69f4938262ac8190b41f922d0407d272 |
completed | May 1, 2026, 11:50 a.m. |
Created at: April 21, 2026, 9:49 p.m.