Triple
T22300529
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Torbay Council |
E551241
|
entity |
| Predicate | hasPoliticalLeadershipModel |
P147975
|
FINISHED |
| Object | leader and cabinet |
—
|
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: leader and cabinet | Statement: [Torbay Council, hasPoliticalLeadershipModel, leader and cabinet]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPoliticalLeadershipModel Context triple: [Torbay Council, hasPoliticalLeadershipModel, leader and cabinet]
-
A.
hasLeaderInGovernment
Indicates that one entity serves as the leader or head of government for another entity.
-
B.
hadLeadershipFrom
Indicates that one entity received leadership, guidance, or direction from another entity.
-
C.
hasLeadershipExperienceIn
Indicates that an entity possesses prior leadership experience specifically within a given domain, context, or organization.
-
D.
hasPoliticalPower
Indicates that one entity holds authority or influence to make, shape, or enforce political decisions over another entity or within a political system.
-
E.
hasCivicLeader
Indicates that an entity serves as the civic leader (such as a mayor or equivalent public official) of another entity, typically a city or municipality.
- 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_69e11e46c0188190800181a4233f28fe |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f1572399148190853c4e91fcf9f38c |
completed | April 29, 2026, 12:56 a.m. |
| PD | Predicate disambiguation | batch_69e72ffa438481908f80879aef2a589b |
completed | April 21, 2026, 8:06 a.m. |
| PDg | Predicate description generation | batch_69e75dc7b08081909d64441e979c2fa4 |
completed | April 21, 2026, 11:21 a.m. |
Created at: April 16, 2026, 8:41 p.m.