Triple
T27455461
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wijnegem |
E692578
|
entity |
| Predicate | hasShoppingMallRank |
P169936
|
FINISHED |
| Object | one of the largest in Benelux |
—
|
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: one of the largest in Benelux | Statement: [Wijnegem, hasShoppingMallRank, one of the largest in Benelux]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasShoppingMallRank Context triple: [Wijnegem, hasShoppingMallRank, one of the largest in Benelux]
-
A.
hasShoppingMall
Indicates that one entity possesses, contains, or includes a shopping mall within its area or domain.
-
B.
hasShoppingMallName
Indicates that an entity (such as a shopping mall) is associated with or identified by a specific name.
-
C.
isIndoorMall
Indicates that a shopping mall is located indoors, typically enclosed within a single building or connected interior space.
-
D.
hasShoppingDistrictType
Indicates that an entity is associated with a particular type or category of shopping district.
-
E.
hasShoppingDistrict
Indicates that a place contains or is associated with a designated area where multiple shops and commercial retail activities are concentrated.
- 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_69ef5207903881909427745cda05d27a |
completed | April 27, 2026, 12:09 p.m. |
| NER | Named-entity recognition | batch_69f688d015908190ad5df37030ecf332 |
completed | May 2, 2026, 11:29 p.m. |
| PD | Predicate disambiguation | batch_69f68609c0b08190a8e1238a4d97c270 |
completed | May 2, 2026, 11:17 p.m. |
| PDg | Predicate description generation | batch_69f688034580819086a0f9100645f8ba |
completed | May 2, 2026, 11:25 p.m. |
Created at: April 27, 2026, 12:48 p.m.