Triple
T28019620
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rechberghausen |
E707648
|
entity |
| Predicate | hasNeighbouringAdministrativeUnitType |
P193775
|
FINISHED |
| Object | municipality |
—
|
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: municipality | Statement: [Rechberghausen, hasNeighbouringAdministrativeUnitType, municipality]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNeighbouringAdministrativeUnitType Context triple: [Rechberghausen, hasNeighbouringAdministrativeUnitType, municipality]
-
A.
hasNeighbouringDivision
Indicates that one division is directly adjacent to and shares a boundary with another division.
-
B.
neighbouringMunicipality
Indicates that one municipality directly borders and is adjacent to another municipality.
-
C.
hasNeighboringLGA
Indicates that one local government area is geographically adjacent to or directly borders another local government area.
-
D.
hasNeighbouringUnit
Indicates that one unit is directly adjacent to and shares a boundary or side with another unit.
-
E.
hasNeighbouringState
Indicates that one state shares a common border or is directly adjacent geographically to another state.
- 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_69ef96baf3a881909a2b63844185dddd |
completed | April 27, 2026, 5:02 p.m. |
| NER | Named-entity recognition | batch_69fd553d7cb881908d243e7a9f30ac85 |
completed | May 8, 2026, 3:15 a.m. |
| PD | Predicate disambiguation | batch_69fd514dcb1c81908333c70d7edd79c9 |
completed | May 8, 2026, 2:58 a.m. |
| PDg | Predicate description generation | batch_69fd553c01488190b9fda48b4a728f04 |
completed | May 8, 2026, 3:15 a.m. |
Created at: April 27, 2026, 8:09 p.m.