Triple
T23414668
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | IFS Chengdu |
E560169
|
entity |
| Predicate | cateredCustomerSegment |
P19115
|
FINISHED |
| Object | affluent shoppers |
—
|
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: affluent shoppers | Statement: [IFS Chengdu, cateredCustomerSegment, affluent shoppers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cateredCustomerSegment Context triple: [IFS Chengdu, cateredCustomerSegment, affluent shoppers]
-
A.
categoryOfPeopleServed
chosen
Indicates the type or group of people that are the primary recipients or beneficiaries of a service or activity.
-
B.
customerGroup
Indicates a relationship in which an entity belongs to, is classified under, or is associated with a particular group of customers.
-
C.
customerType
Indicates the classification or category assigned to a customer based on their characteristics, status, or relationship with a business.
-
D.
passengerSegments
Indicates a relationship where a journey or trip is divided into distinct legs or segments that a passenger travels through.
-
E.
majorCustomer
Indicates that one entity is a primary or high-value customer of another entity, typically contributing a significant portion of business or revenue.
- 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_69e2454b3a5881909c64773dc8a5d289 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f1a514b1d08190bbde2c3714c996fd |
completed | April 29, 2026, 6:28 a.m. |
| PD | Predicate disambiguation | batch_69f061ed34288190a2e5e8cae03b0095 |
completed | April 28, 2026, 7:29 a.m. |
Created at: April 17, 2026, 5:39 p.m.