Triple
T1375767
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shibuya Scramble Square |
E29217
|
entity |
| Predicate | floorUseDistribution |
P27104
|
FINISHED |
| Object | lower floors for retail and restaurants |
—
|
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: lower floors for retail and restaurants | Statement: [Shibuya Scramble Square, floorUseDistribution, lower floors for retail and restaurants]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: floorUseDistribution Context triple: [Shibuya Scramble Square, floorUseDistribution, lower floors for retail and restaurants]
-
A.
floorType
Indicates the type or material classification of a floor associated with an entity.
-
B.
hasFloorMaterial
Indicates that an entity’s floor is made of, covered with, or constructed from a specified material.
-
C.
hasFlooring
Indicates that one entity is equipped with or covered by a particular type of flooring material provided by another entity.
-
D.
floor
Indicates that one entity is located on or forms the walking surface (the floor) beneath another entity within a space.
-
E.
floorCount
Indicates the number of floors or levels that a building or structure has.
- 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_69a498d883a48190bfdca525296ef7ee |
completed | March 1, 2026, 7:51 p.m. |
| NER | Named-entity recognition | batch_69a4c2f9b51c8190ad52fd8c151499be |
completed | March 1, 2026, 10:51 p.m. |
| PD | Predicate disambiguation | batch_69a4befcabdc8190a9f05d002603f81c |
completed | March 1, 2026, 10:34 p.m. |
| PDg | Predicate description generation | batch_69a4c0335f7081908d50046ced4cdee0 |
completed | March 1, 2026, 10:39 p.m. |
Created at: March 1, 2026, 7:59 p.m.