Triple
T26017783
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Disruption |
E647068
|
entity |
| Predicate | numberOfMinistersWhoLeft |
P36242
|
FINISHED |
| Object | over 450 |
—
|
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: over 450 | Statement: [The Disruption, numberOfMinistersWhoLeft, over 450]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfMinistersWhoLeft Context triple: [The Disruption, numberOfMinistersWhoLeft, over 450]
-
A.
hasNumberOfMinisters
chosen
Indicates the specific count of ministers associated with an entity, such as a government, cabinet, or organization.
-
B.
numberOfMinistersLimit
Indicates a constraint specifying the maximum allowable number of ministers in a given context or governing body.
-
C.
resignedFromCabinetOver
Indicates that a person resigned from a governmental cabinet specifically because of, or in protest over, a particular issue, event, or circumstance.
-
D.
numberOfTermsAsChiefMinister
Indicates the count of separate terms an individual has served in the role of Chief Minister.
-
E.
hasMinister
Indicates that one entity serves as the minister (political, religious, or administrative official) responsible for or associated with another entity.
- 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_69e77e8aa65881909ca58918f29ab2a0 |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69fd389cb28c819099a77e28d25f258a |
completed | May 8, 2026, 1:13 a.m. |
| PD | Predicate disambiguation | batch_69fd3826d8048190ada79a5868d1d7f3 |
completed | May 8, 2026, 1:11 a.m. |
Created at: April 22, 2026, 9:03 a.m.