Triple
T26410430
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wilmington Metropolitan Division |
E663943
|
entity |
| Predicate | hasUrbanCommunities |
P156670
|
FINISHED |
| Object | Wilmington urban area |
—
|
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: Wilmington urban area | Statement: [Wilmington Metropolitan Division, hasUrbanCommunities, Wilmington urban area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasUrbanCommunities Context triple: [Wilmington Metropolitan Division, hasUrbanCommunities, Wilmington urban area]
-
A.
hasUrbanVillages
Indicates that an entity contains or includes one or more designated urban villages within its area or jurisdiction.
-
B.
hasUrbanLocalities
Indicates that an entity possesses or includes one or more urban localities within its jurisdiction or scope.
-
C.
hasUrbanSectionsIn
Indicates that an entity includes or contains sections that are classified as urban within a specified area or region.
-
D.
hasUrbanUnits
chosen
Indicates that an entity possesses or includes one or more urban units (such as cities, towns, or urbanized areas) within its scope or structure.
-
E.
hasUrbanDistrictCount
Indicates the number of urban districts associated with a given entity.
- 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_69ee883931888190901be96d75ee23cc |
completed | April 26, 2026, 9:48 p.m. |
| NER | Named-entity recognition | batch_69f621fcea1481909b6f8b3af1ee6820 |
completed | May 2, 2026, 4:10 p.m. |
| PD | Predicate disambiguation | batch_69f620debeb48190b7db395fb86cf8d9 |
completed | May 2, 2026, 4:05 p.m. |
Created at: April 26, 2026, 11:37 p.m.