Triple
T28115297
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | De Meent (shopping center, Papendrecht) |
E710604
|
entity |
| Predicate | isCentralShoppingAreaOf |
P4285
|
FINISHED |
| Object | Papendrecht |
—
|
NE NERFINISHED |
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: Papendrecht | Statement: [De Meent (shopping center, Papendrecht), isCentralShoppingAreaOf, Papendrecht]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isCentralShoppingAreaOf Context triple: [De Meent (shopping center, Papendrecht), isCentralShoppingAreaOf, Papendrecht]
-
A.
hasShoppingDistrictName
Indicates that an entity’s shopping district is identified by a specific name.
-
B.
isShoppingDistrict
Indicates that a location functions primarily as a shopping district, characterized by a concentration of retail stores and commercial shopping activity.
-
C.
hasShoppingDistrict
chosen
Indicates that a place contains or is associated with a designated area where multiple shops and commercial retail activities are concentrated.
-
D.
hasCommercialCenterType
Indicates that an entity has or is associated with a specific type or category of commercial center (e.g., mall, shopping district, business park).
-
E.
locationOfShoppingCenter
Indicates that a specified place is the geographic location where a particular shopping center is situated.
- 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_69ef9b72f63081909dfbc2c1ddae86c6 |
completed | April 27, 2026, 5:22 p.m. |
| NER | Named-entity recognition | batch_69f65876c52c8190bc889c7a67bd07f3 |
completed | May 2, 2026, 8:03 p.m. |
| PD | Predicate disambiguation | batch_69f6575d89788190aca478e4aea05a65 |
completed | May 2, 2026, 7:58 p.m. |
Created at: April 27, 2026, 9:13 p.m.