Triple
T942386
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jens Stoltenberg |
E20334
|
entity |
| Predicate | officeTerm |
P22017
|
FINISHED |
| Object | first term as Prime Minister of 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: first term as Prime Minister of Norway | Statement: [Jens Stoltenberg, officeTerm, first term as Prime Minister of Norway]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: officeTerm Context triple: [Jens Stoltenberg, officeTerm, first term as Prime Minister of Norway]
-
A.
office
Indicates that an entity holds or occupies an official position, role, or post within an organization or institution.
-
B.
officeCategory
Indicates the classification or type of an office within a defined categorization scheme.
-
C.
officeScope
Indicates that a relationship, authority, or action is limited to, defined within, or applicable only in the context of a particular office or official position.
-
D.
equivalentOffice
Indicates that two offices are considered functionally or formally the same position, role, or authority, even if they differ in name or jurisdiction.
-
E.
worksWithOffice
Indicates that an entity collaborates or is professionally associated with a particular office or office-based organization.
- 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_69a493b0270c81909e6c9ce310f6aa55 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b3a1a4888190997adf56eb761431 |
completed | March 1, 2026, 9:46 p.m. |
| PD | Predicate disambiguation | batch_69a4b29dc8dc8190b9d33f70f8563d61 |
completed | March 1, 2026, 9:41 p.m. |
| PDg | Predicate description generation | batch_69a4b344f6f48190ba03ce593c94176b |
completed | March 1, 2026, 9:44 p.m. |
Created at: March 1, 2026, 7:40 p.m.