Triple
T30411720
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Subang |
E773636
|
entity |
| Predicate | hasNearbyShoppingFacilities |
P191961
|
FINISHED |
| Object | Subang Parade (nearby in Subang Jaya) |
—
|
NE NERFINISHED |
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: Subang Parade (nearby in Subang Jaya) | Statement: [Subang, hasNearbyShoppingFacilities, Subang Parade (nearby in Subang Jaya)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNearbyShoppingFacilities Context triple: [Subang, hasNearbyShoppingFacilities, Subang Parade (nearby in Subang Jaya)]
-
A.
hasNearbyCommercialFacilities
chosen
Indicates that a place is located close to one or more commercial facilities, such as shops, restaurants, or other businesses.
-
B.
hasNearbyFacility
Indicates that one entity is located close to or in the vicinity of a particular facility.
-
C.
hasConvenienceStore
Indicates that one entity possesses, contains, or is associated with a convenience store.
-
D.
hasShoppingDistrict
Indicates that a place contains or is associated with a designated area where multiple shops and commercial retail activities are concentrated.
-
E.
hasOutletNear
Indicates that one entity has a physical outlet or branch located in close proximity to another specified location or entity.
- 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_69f22490b8b48190ab10c886a8d58c89 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69fea5e828cc8190a9b755a645dc56d2 |
completed | May 9, 2026, 3:11 a.m. |
| PD | Predicate disambiguation | batch_69fea36443f08190b2aced9b4a0525fd |
completed | May 9, 2026, 3 a.m. |
Created at: April 29, 2026, 8:05 p.m.