Triple
T12293624
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lørenskog |
E293027
|
entity |
| Predicate | hasCountySeatRole |
P31116
|
FINISHED |
| Object | no county seat |
—
|
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: no county seat | Statement: [Lørenskog, hasCountySeatRole, no county seat]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCountySeatRole Context triple: [Lørenskog, hasCountySeatRole, no county seat]
-
A.
hasCountySeatWithRole
chosen
Indicates that a county has a designated county seat that fulfills a specific administrative or governmental role.
-
B.
hasCountySeatOf
Indicates that a place serves as the administrative county seat (capital) of a specified county.
-
C.
hasCountySeatOn
Indicates that a county’s administrative center (county seat) is located on or adjacent to a specified geographic feature or infrastructure.
-
D.
hasCountySeatCity
Indicates that a county has a specific city that serves as its official administrative center or county seat.
-
E.
hasCountySeatCounty
Indicates that a county seat is administratively associated with and serves as the seat of government for a specific county.
- 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_69d6ab690ad081908c0ed3870ec82d53 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d91d23def88190adbaa282dd03d6c6 |
completed | April 10, 2026, 3:54 p.m. |
| PD | Predicate disambiguation | batch_69d91c4ec6c4819085880bdefdd0f354 |
completed | April 10, 2026, 3:50 p.m. |
Created at: April 8, 2026, 9:52 p.m.