Triple
T28623165
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Select Citywalk Mall |
E724440
|
entity |
| Predicate | hasBeautyAndCosmeticsStores |
P150941
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Select Citywalk Mall, hasBeautyAndCosmeticsStores, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBeautyAndCosmeticsStores Context triple: [Select Citywalk Mall, hasBeautyAndCosmeticsStores, yes]
-
A.
hasHealthAndBeautyStores
chosen
Indicates that an entity operates, controls, or is associated with one or more stores that sell health and beauty products.
-
B.
includesCosmetics
Indicates that one entity contains or encompasses cosmetic products or items as part of its contents or offerings.
-
C.
hasJewelleryStores
Indicates that one entity possesses or contains one or more jewellery retail stores associated with it.
-
D.
hasRetailBoutiquesIn
Indicates that an entity operates or maintains retail boutiques located within a specified place or region.
-
E.
cosmeticCategory
Indicates that one entity is classified as belonging to a particular cosmetic or beauty product category defined by the other 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_69f01d822ac08190932de59ec2268ed2 |
completed | April 28, 2026, 2:37 a.m. |
| NER | Named-entity recognition | batch_69f6cee45590819086e489bfccbe4ac3 |
completed | May 3, 2026, 4:28 a.m. |
| PD | Predicate disambiguation | batch_69f6cc1188708190b8f0f56e595e6057 |
completed | May 3, 2026, 4:16 a.m. |
Created at: April 28, 2026, 4:34 a.m.