Triple
T3932000
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | First Balkenende cabinet |
E90814
|
entity |
| Predicate | durationInOffice |
P36144
|
FINISHED |
| Object | approximately 10 months |
—
|
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: approximately 10 months | Statement: [First Balkenende cabinet, durationInOffice, approximately 10 months]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: durationInOffice Context triple: [First Balkenende cabinet, durationInOffice, approximately 10 months]
-
A.
termInOffice
Indicates the period during which an individual officially holds a particular office or position.
-
B.
numberOfTimesInOffice
Indicates the count of separate terms or periods an entity has held a particular office or position.
-
C.
succeededInOffice
Indicates that one officeholder directly followed another in holding the same official position.
-
D.
timeInOfficeBeginsIn
Indicates the point in time or date when an entity’s term, tenure, or period in office starts.
-
E.
timeInOfficeRelation
chosen
Indicates a temporal relationship specifying the duration or period that an entity holds or held a particular office or position.
- 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_69aed95f26e0819094b0e71974543a19 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeedaaf3c881909539831bf3a8bf10 |
completed | March 9, 2026, 3:56 p.m. |
| PD | Predicate disambiguation | batch_69aee7625ad4819097e4e8a168c19274 |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:23 p.m.