Triple
T2462166
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Universal Studios Singapore |
E54555
|
entity |
| Predicate | numberOfThemedZones |
P40661
|
FINISHED |
| Object | 7 |
—
|
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: 7 | Statement: [Universal Studios Singapore, numberOfThemedZones, 7]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfThemedZones Context triple: [Universal Studios Singapore, numberOfThemedZones, 7]
-
A.
hasDRSZones
Indicates that one entity possesses, defines, or is associated with specific DRS (Disaster Recovery Site or similarly defined) zones.
-
B.
numberOfRegions
Indicates the total count of distinct regions associated with or contained within a given entity.
-
C.
numberOfAreaBoards
Indicates the total count of area boards associated with or defined for a given entity or context.
-
D.
numberOfVenues
Indicates the total count of venues associated with a given entity or context.
-
E.
numberOfDomes
Indicates the quantity of domes that an entity possesses or is associated with.
- 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_69ab49dee84c819096b50a0049c347ac |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abd49c5aa081909ab4f726a458b77f |
completed | March 7, 2026, 7:32 a.m. |
| PD | Predicate disambiguation | batch_69abd0b199488190aa381b36593ae1ac |
completed | March 7, 2026, 7:16 a.m. |
| PDg | Predicate description generation | batch_69abd49b5d2481908817aeb171e2bd61 |
completed | March 7, 2026, 7:32 a.m. |
Created at: March 6, 2026, 9:44 p.m.