Triple
T20568567
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bondevik's First Cabinet |
E505028
|
entity |
| Predicate | timeInOfficeInYearsApprox |
P87233
|
FINISHED |
| Object | 2.4 |
—
|
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: 2.4 | Statement: [Bondevik's First Cabinet, timeInOfficeInYearsApprox, 2.4]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: timeInOfficeInYearsApprox Context triple: [Bondevik's First Cabinet, timeInOfficeInYearsApprox, 2.4]
-
A.
timeInOfficeCharacteristic
chosen
Indicates a characteristic or attribute specifically related to the duration or period an entity spends in office or in a particular official role.
-
B.
numberOfTermInOffice
Indicates the specific ordinal count of how many terms an entity has served in a particular office or position.
-
C.
timeInOfficeBeginsIn
Indicates the point in time or date when an entity’s term, tenure, or period in office starts.
-
D.
termInOffice
Indicates the period during which an individual officially holds a particular office or position.
-
E.
timeInNationalGovernment
Indicates the duration that an entity has served within a national-level government.
- 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_69e0b4b721588190993ac7b0a9be2736 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6a7a3fdc08190a34dcf4c4e51f078 |
completed | April 20, 2026, 10:24 p.m. |
| PD | Predicate disambiguation | batch_69e59ff0116c8190a163ff28ed01430a |
completed | April 20, 2026, 3:39 a.m. |
Created at: April 16, 2026, 11:39 a.m.