Triple
T23707747
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Schwarzhäusern |
E585771
|
entity |
| Predicate | hasNeighbouringEntityType |
P75079
|
FINISHED |
| Object | Swiss municipalities |
—
|
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: Swiss municipalities | Statement: [Schwarzhäusern, hasNeighbouringEntityType, Swiss municipalities]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNeighbouringEntityType Context triple: [Schwarzhäusern, hasNeighbouringEntityType, Swiss municipalities]
-
A.
hasNeighbouringUnit
Indicates that one unit is directly adjacent to and shares a boundary or side with another unit.
-
B.
hasNeighboringFeature
Indicates that one feature is located adjacent to or directly next to another feature in space.
-
C.
hasNeighboringObject
Indicates that one object is located adjacent to or directly next to another object in space.
-
D.
hasNeighborRelationshipWith
chosen
Indicates that one entity is located adjacent to or directly next to another entity, sharing a neighbor relationship.
-
E.
hasNearbySiteType
Indicates that one entity has another entity of a specified site type located in its close physical vicinity.
- 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_69e24905f77881908194d645676acd60 |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1b68868ac8190824cdd7eb9fb2f06 |
completed | April 29, 2026, 7:43 a.m. |
| PD | Predicate disambiguation | batch_69f155e4b1148190836ede4741dcb888 |
completed | April 29, 2026, 12:50 a.m. |
Created at: April 17, 2026, 6:53 p.m.