Triple
T4516725
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lenasia |
E102169
|
entity |
| Predicate | hasCommercialAreaType |
P20782
|
FINISHED |
| Object | shopping centres |
—
|
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: shopping centres | Statement: [Lenasia, hasCommercialAreaType, shopping centres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCommercialAreaType Context triple: [Lenasia, hasCommercialAreaType, shopping centres]
-
A.
hasAreaType
Indicates that an entity is associated with a specific kind or classification of area (e.g., urban, rural, coastal).
-
B.
hasBusinessDistrict
Indicates that a place or administrative area contains or includes a designated business district within its boundaries.
-
C.
hasIndustrialAreaType
Indicates that an entity’s industrial area is classified as a specific type or category of industrial zone.
-
D.
commercialArea
chosen
Indicates that the location or region is designated primarily for commercial activities such as businesses, shops, or services.
-
E.
hasRetailArea
Indicates that an entity possesses or includes a designated space used for retail or commercial sales activities.
- 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_69bd43d6251c81909deecce3e6e9d69c |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd5726983c8190bca116eeee54241c |
completed | March 20, 2026, 2:18 p.m. |
| PD | Predicate disambiguation | batch_69bd521abea48190b3e758a1f98dd55e |
completed | March 20, 2026, 1:56 p.m. |
Created at: March 20, 2026, 1:02 p.m.