Triple
T24660324
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | County Governor of Nordland |
E610517
|
entity |
| Predicate | numberOfSimilarOfficesInNorway |
P158085
|
FINISHED |
| Object | one of several county governors in Norway |
—
|
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: one of several county governors in Norway | Statement: [County Governor of Nordland, numberOfSimilarOfficesInNorway, one of several county governors in Norway]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfSimilarOfficesInNorway Context triple: [County Governor of Nordland, numberOfSimilarOfficesInNorway, one of several county governors in Norway]
-
A.
numberOfOffices
Indicates the total count of offices associated with a given entity.
-
B.
comparableOffice
Indicates that two offices are sufficiently similar in relevant characteristics (such as size, function, or status) to be meaningfully compared to each other.
-
C.
officeNameInNynorsk
Indicates the name of an office expressed in the Nynorsk written standard of the Norwegian language.
-
D.
hasNumberOfRegionalOffices
Indicates the quantity of regional offices that an entity possesses or operates.
-
E.
cabinetNumberInNorway
Indicates the specific ordinal number of a Norwegian government cabinet within the historical sequence of cabinets in Norway.
- 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_69e2c4d453248190a020354e93ef6282 |
completed | April 17, 2026, 11:40 p.m. |
| NER | Named-entity recognition | batch_69f464b4c9b0819085daa00c7c3b8b76 |
completed | May 1, 2026, 8:30 a.m. |
| PD | Predicate disambiguation | batch_69f45cf017a88190b4985b11159c907d |
completed | May 1, 2026, 7:57 a.m. |
| PDg | Predicate description generation | batch_69f464ae42e88190b3549fdf4e0b425e |
completed | May 1, 2026, 8:30 a.m. |
Created at: April 18, 2026, 2:34 a.m.