Triple
T11063121
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | House of Good Fortune |
E261556
|
entity |
| Predicate | hasMerchandiseStyle |
P1609
|
FINISHED |
| Object | Chinese-inspired design |
—
|
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: Chinese-inspired design | Statement: [House of Good Fortune, hasMerchandiseStyle, Chinese-inspired design]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMerchandiseStyle Context triple: [House of Good Fortune, hasMerchandiseStyle, Chinese-inspired design]
-
A.
hasPromotionStyle
Indicates the manner or approach used to promote or market something in relation to another entity.
-
B.
hasContractStyle
Indicates that one entity is associated with or characterized by a particular contract style or contractual format.
-
C.
hasStyle
chosen
Indicates that an entity possesses, exhibits, or is characterized by a particular style or manner.
-
D.
hasMerchandiseTieIn
Indicates that one entity has a commercial or promotional product or line (merchandise) that is directly tied to, branded with, or derived from another entity.
-
E.
hasGarment
Indicates that one entity possesses, wears, or is associated with a particular garment.
- 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_69d6aa98650481908609c7c56bfa7902 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d798eb838c819089a89c55209c0295 |
completed | April 9, 2026, 12:17 p.m. |
| PD | Predicate disambiguation | batch_69d74411d9e881908c0eeafa0f38e4b6 |
completed | April 9, 2026, 6:15 a.m. |
Created at: April 8, 2026, 9:26 p.m.