Triple
T30955980
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 恒隆广场 |
E788676
|
entity |
| Predicate | 客群定位 |
P82393
|
FINISHED |
| Object | 高端消费人群 |
—
|
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: 高端消费人群 | Statement: [恒隆广场, 客群定位, 高端消费人群]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 客群定位 Context triple: [恒隆广场, 客群定位, 高端消费人群]
-
A.
targetMarket
Indicates the group of consumers or organizations that a product, service, or campaign is specifically intended and designed to reach.
-
B.
targetsGroup
Indicates that an action, influence, or effect is directed toward a specific group as its intended recipient or focus.
-
C.
targetAudienceTheme
Indicates the thematic focus or type of audience that a work, message, or product is specifically intended to appeal to or address.
-
D.
marketSegmentType
Indicates the specific category or segment of the market that an entity, product, or service is targeted toward or associated with.
-
E.
customerGroup
chosen
Indicates a relationship in which an entity belongs to, is classified under, or is associated with a particular group of customers.
- 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_69f224c28c1881908c33b45d689f1724 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f6953bafb88190a860e9c68a3dd4b2 |
completed | May 3, 2026, 12:22 a.m. |
| PD | Predicate disambiguation | batch_69f690ef92308190903a54fc74233269 |
completed | May 3, 2026, 12:03 a.m. |
Created at: April 29, 2026, 8:54 p.m.