Triple
T16848697
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Barkly Regional Council |
E409612
|
entity |
| Predicate | hasMayorOrPresident |
P185
|
FINISHED |
| Object | Mayor of Barkly Regional Council |
—
|
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: Mayor of Barkly Regional Council | Statement: [Barkly Regional Council, hasMayorOrPresident, Mayor of Barkly Regional Council]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMayorOrPresident Context triple: [Barkly Regional Council, hasMayorOrPresident, Mayor of Barkly Regional Council]
-
A.
hasPresident
Indicates that an entity holds the position or role of president for another entity.
-
B.
hasMayor
chosen
Indicates that one entity serves as the mayor of another entity, typically a city, town, or municipality.
-
C.
hasMayorOffice
Indicates that a particular entity serves as the office or official position held by a mayor of another entity.
-
D.
hasMayorTerm
Indicates that a specified individual holds or has held the office of mayor for a particular jurisdiction during a defined term.
-
E.
hasNotableMayor
Indicates that an entity has or had a mayor who is particularly distinguished, prominent, or noteworthy.
- 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_69d883952b048190887740a980b712ed |
completed | April 10, 2026, 4:59 a.m. |
| NER | Named-entity recognition | batch_69e3b377b5d881909f0878dd9957f3bc |
completed | April 18, 2026, 4:38 p.m. |
| PD | Predicate disambiguation | batch_69e32b87b4248190aaddb05e88452356 |
completed | April 18, 2026, 6:58 a.m. |
Created at: April 10, 2026, 5:24 a.m.