Triple
T13944372
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Province of Naples (historical) |
E335341
|
entity |
| Predicate | hadAdministrativeRole |
P90489
|
FINISHED |
| Object | local government |
—
|
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: local government | Statement: [Province of Naples (historical), hadAdministrativeRole, local government]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hadAdministrativeRole Context triple: [Province of Naples (historical), hadAdministrativeRole, local government]
-
A.
hasOrganizationalRole
Indicates that an entity holds a specific role, position, or function within an organization.
-
B.
hasGoverningRole
chosen
Indicates that one entity holds an official position of authority, control, or governance over another entity or domain.
-
C.
hasPoliticalRole
Indicates that an entity holds, has held, or is assigned a specific political office, function, or position in relation to another entity or context.
-
D.
servedInRole
Indicates that one entity performed duties or held a position within a specified role or office in relation to another entity.
-
E.
hadStaffRole
Indicates that an entity served in a specific staff role or position for another entity during some period.
- 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_69d81c6081b88190b53e317c3370c8fe |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2e0f6f3c8190a64058b732b0ac52 |
completed | April 14, 2026, 12:07 p.m. |
| PD | Predicate disambiguation | batch_69de05a3ccf88190b45c742db483fa08 |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 9, 2026, 10:17 p.m.