Triple
T9870887
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nanjing West Road |
E239952
|
entity |
| Predicate | shoppingCategory |
P72821
|
FINISHED |
| Object | luxury shopping |
—
|
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: luxury shopping | Statement: [Nanjing West Road, shoppingCategory, luxury shopping]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: shoppingCategory Context triple: [Nanjing West Road, shoppingCategory, luxury shopping]
-
A.
commercialCategory
chosen
Indicates the type of commercial classification or business category under which an entity or transaction is grouped.
-
B.
shopSpecialty
Indicates that a shop primarily focuses on or is specially known for offering a particular type of product or service.
-
C.
retailConcept
Indicates that one entity represents a retail-related concept, model, or framework that characterizes or defines the nature of another entity’s retail activity or context.
-
D.
tradeMedium
Indicates that one entity serves as the medium or instrument through which another entity conducts trade or exchange transactions.
-
E.
usedInECommerce
Indicates that something is employed or applied within the context of electronic commerce activities or systems.
- 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_69ca84e7506c819095cbde4ff16512bb |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb3d62628819094786a49b9bcd09b |
completed | April 2, 2026, 12:09 a.m. |
| PD | Predicate disambiguation | batch_69cd1d7621d48190aa6a6f34399514b0 |
completed | April 1, 2026, 1:28 p.m. |
Created at: March 30, 2026, 8:36 p.m.