Triple
T8161720
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shanghai Urban Planning Exhibition Center |
E190590
|
entity |
| Predicate | totalFloorsAboveGround |
P78480
|
FINISHED |
| Object | 5 |
—
|
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: 5 | Statement: [Shanghai Urban Planning Exhibition Center, totalFloorsAboveGround, 5]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: totalFloorsAboveGround Context triple: [Shanghai Urban Planning Exhibition Center, totalFloorsAboveGround, 5]
-
A.
hasFloorsAboveGround
chosen
Indicates that an entity (typically a building or structure) possesses a specified number of floors that are located above ground level.
-
B.
numberOfFloors
Indicates the total count of distinct floor levels that a building or structure has.
-
C.
floorCount
Indicates the number of floors or levels that a building or structure has.
-
D.
floorCountIncludingBasement
Indicates the total number of floors in a building, counting all above-ground levels plus any basement levels.
-
E.
numberOfResidentialFloors
Indicates the total count of floors in a building that are designated for residential use.
- 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_69ca82c0ef14819083713f4473dd847c |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb4556b45c819089eb15ad027b036a |
completed | March 31, 2026, 3:53 a.m. |
| PD | Predicate disambiguation | batch_69cb36a4c40c81909f60aef0e1624c13 |
completed | March 31, 2026, 2:51 a.m. |
Created at: March 30, 2026, 5:38 p.m.