Triple
T5837772
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chief Administrative Officer of Oslo |
E129513
|
entity |
| Predicate | hasTitleInNorwegianBokmål |
P61994
|
FINISHED |
| Object | rådmann i Oslo |
—
|
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: rådmann i Oslo | Statement: [Chief Administrative Officer of Oslo, hasTitleInNorwegianBokmål, rådmann i Oslo]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTitleInNorwegianBokmål Context triple: [Chief Administrative Officer of Oslo, hasTitleInNorwegianBokmål, rådmann i Oslo]
-
A.
titleInNorwegian
chosen
Indicates that one entity is the title of another entity expressed in the Norwegian language.
-
B.
hasOfficialNameInNorwegianBokmål
Indicates that an entity has an official name expressed in the Norwegian Bokmål language.
-
C.
hasNameInNorwegian
Indicates that an entity is associated with a specific name expressed in the Norwegian language.
-
D.
hasOfficialNameInNorwegianNynorsk
Indicates that an entity has an official name expressed in the Norwegian Nynorsk language.
-
E.
hasTitleInAfrikaans
Indicates that an entity has a specific title expressed in the Afrikaans language.
- 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_69c0084af79c81908af128ccc29983d0 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c044ab0a048190b84be40fb13c0f50 |
completed | March 22, 2026, 7:36 p.m. |
| PD | Predicate disambiguation | batch_69c03341e5888190a5f219b6f92cb161 |
completed | March 22, 2026, 6:21 p.m. |
Created at: March 22, 2026, 3:54 p.m.