Triple
T22662653
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Raffles City Singapore |
E559702
|
entity |
| Predicate | hasNumberOfShoppingLevels |
P7355
|
FINISHED |
| Object | multiple retail floors |
—
|
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: multiple retail floors | Statement: [Raffles City Singapore, hasNumberOfShoppingLevels, multiple retail floors]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfShoppingLevels Context triple: [Raffles City Singapore, hasNumberOfShoppingLevels, multiple retail floors]
-
A.
hasMultipleLevels
Indicates that something is organized into more than one hierarchical or structural level.
-
B.
hasNumberOfLevels
chosen
Indicates that an entity possesses a specified count of distinct levels or tiers.
-
C.
numberOfLevels
Indicates the total count of hierarchical layers, stages, or floors associated with an entity.
-
D.
hasAisles
Indicates that a location or structure contains one or more aisles as part of its internal layout or organization.
-
E.
numberOfSeatingLevels
Indicates the total count of distinct seating levels or tiers associated with a venue, structure, or seating arrangement.
- 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_69e2454a158c819093b8e35f5045efb6 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f17660c0c88190bed9fa8f6517eec4 |
completed | April 29, 2026, 3:09 a.m. |
| PD | Predicate disambiguation | batch_69ee62a6245881909506ff502da14137 |
completed | April 26, 2026, 7:08 p.m. |
Created at: April 17, 2026, 3:08 p.m.