Triple
T31012121
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bokkos Local Government Area |
E790233
|
entity |
| Predicate | hasMajorOccupation |
P150047
|
FINISHED |
| Object | Subsistence farming |
—
|
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: Subsistence farming | Statement: [Bokkos Local Government Area, hasMajorOccupation, Subsistence farming]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMajorOccupation Context triple: [Bokkos Local Government Area, hasMajorOccupation, Subsistence farming]
-
A.
hasTypicalOccupation
Indicates that an entity commonly or characteristically works in a particular job or profession.
-
B.
hasMajorEmployerType
Indicates the type or category of major employer associated with an entity.
-
C.
significantOccupation
chosen
Indicates that an occupation plays a major or defining role in an entity’s life, status, or identity.
-
D.
hasMajorEmployerHistory
Indicates that an entity has a documented history of employment with a major or significant employer.
-
E.
hasOccupationInWork
Indicates that an entity holds or performs a specific occupation within a particular work, project, or creative production.
- 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_69f224c73ca48190a1e46cb58ad4045b |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69fff09dae088190bd8460060d778feb |
completed | May 10, 2026, 2:42 a.m. |
| PD | Predicate disambiguation | batch_69fff0027c5c8190baa5c7a15852cbe0 |
completed | May 10, 2026, 2:40 a.m. |
Created at: April 29, 2026, 8:57 p.m.