Triple
T12896463
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shinjuku Nomura Building |
E308505
|
entity |
| Predicate | floorCountUnderground |
P1514
|
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: [Shinjuku Nomura Building, floorCountUnderground, 5]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: floorCountUnderground Context triple: [Shinjuku Nomura Building, floorCountUnderground, 5]
-
A.
hasUndergroundLevel
Indicates that one entity possesses or includes a level, floor, or section that is located below ground level.
-
B.
floorCount
chosen
Indicates the number of floors or levels that a building or structure has.
-
C.
floorCountIncludingBasement
Indicates the total number of floors in a building, counting all above-ground levels plus any basement levels.
-
D.
hasUndergroundVestibule
Indicates that one entity possesses or includes an underground vestibule space connected to it.
-
E.
floorCountApproximate
Indicates an approximate or estimated number of floors associated with a building or structure.
- 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_69d7bdf7c1f0819098102569a8d8cbf5 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d9717d859481908957510babac2d69 |
completed | April 10, 2026, 9:54 p.m. |
| PD | Predicate disambiguation | batch_69d96fa776648190b9b5c30722ea50b6 |
completed | April 10, 2026, 9:46 p.m. |
Created at: April 9, 2026, 5:40 p.m.