Triple
T26741329
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Niederscheld |
E674266
|
entity |
| Predicate | hasUrbanHierarchyRole |
P8236
|
FINISHED |
| Object | subdivision of Dillenburg |
—
|
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: subdivision of Dillenburg | Statement: [Niederscheld, hasUrbanHierarchyRole, subdivision of Dillenburg]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasUrbanHierarchyRole Context triple: [Niederscheld, hasUrbanHierarchyRole, subdivision of Dillenburg]
-
A.
hasUrbanRole
chosen
Indicates that an entity plays a specific functional or social role within an urban or city context.
-
B.
hasStreetHierarchyRole
Indicates that an entity holds a specific functional or positional role within a defined street hierarchy.
-
C.
hasUrbanRelation
Indicates a relationship where one entity is connected to another through an urban context, such as city-based location, influence, or interaction.
-
D.
hasCityRole
Indicates that an entity holds or is assigned a specific role, function, or status within a particular city.
-
E.
hasUrbanFunction
Indicates that an entity serves a specific role or purpose within an urban context, such as providing services, infrastructure, or activities typical of a city environment.
- 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_69eecda63a3881908095c47900692e65 |
completed | April 27, 2026, 2:44 a.m. |
| NER | Named-entity recognition | batch_69f62d53ad58819080c5227c7a729d15 |
completed | May 2, 2026, 4:58 p.m. |
| PD | Predicate disambiguation | batch_69f62c15952881908a5ea0c25904afec |
completed | May 2, 2026, 4:53 p.m. |
Created at: April 27, 2026, 3:49 a.m.