Triple
T30252603
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Designer Outlet Roermond |
E769247
|
entity |
| Predicate | hasNumberOfBrands |
P193887
|
FINISHED |
| Object | more than 200 |
—
|
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: more than 200 | Statement: [Designer Outlet Roermond, hasNumberOfBrands, more than 200]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfBrands Context triple: [Designer Outlet Roermond, hasNumberOfBrands, more than 200]
-
A.
hasRetailBrands
Indicates that an entity owns, manages, or is associated with one or more retail brands.
-
B.
hasBrandType
Indicates that an entity is associated with or categorized under a particular brand type or classification.
-
C.
hasPrivateLabelBrands
Indicates that an entity offers or is associated with products sold under its own exclusive private-label brands rather than only third-party brands.
-
D.
hasBrandArchitecture
Indicates that one entity defines, structures, or governs the brand architecture (the organized system of brands, sub-brands, and their relationships) of another entity.
-
E.
hasBrandName
Indicates that an entity is associated with or identified by a specific brand name.
- F. None of above. chosen
Provenance (4 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_69f224831dc08190b2e569b987264057 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69fd592e48cc81909d754cc6c4bd99ae |
completed | May 8, 2026, 3:31 a.m. |
| PD | Predicate disambiguation | batch_69fd58b7f9b881909dc099b28d567784 |
completed | May 8, 2026, 3:30 a.m. |
| PDg | Predicate description generation | batch_69fd592cc56081908ce456114d407616 |
completed | May 8, 2026, 3:31 a.m. |
Created at: April 29, 2026, 7:40 p.m.