Triple
T25879187
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Citeureup |
E651996
|
entity |
| Predicate | hasUrbanVillages |
P160296
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Citeureup, hasUrbanVillages, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasUrbanVillages Context triple: [Citeureup, hasUrbanVillages, true]
-
A.
hasUrbanSectionsIn
Indicates that an entity includes or contains sections that are classified as urban within a specified area or region.
-
B.
hasUrbanLocalities
Indicates that an entity possesses or includes one or more urban localities within its jurisdiction or scope.
-
C.
hasUrbanUnits
Indicates that an entity possesses or includes one or more urban units (such as cities, towns, or urbanized areas) within its scope or structure.
-
D.
hasUrbanDistrictCount
Indicates the number of urban districts associated with a given entity.
-
E.
hasUrbanParish
Indicates that an entity is associated with, or contains, a parish located in an urban area.
- 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_69e7ab3ad9d88190841ddcb93ab02e96 |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f6033d54948190a52da9e6bef00afa |
completed | May 2, 2026, 1:59 p.m. |
| PD | Predicate disambiguation | batch_69f5f7fba5248190945acf1561280799 |
completed | May 2, 2026, 1:11 p.m. |
| PDg | Predicate description generation | batch_69f600be0de88190989611e952b03117 |
completed | May 2, 2026, 1:48 p.m. |
Created at: April 22, 2026, 8:13 a.m.