Triple
T32341484
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Siaya County |
E826327
|
entity |
| Predicate | formerGovernor |
P8673
|
FINISHED |
| Object | Cornel Rasanga |
—
|
NE NERFINISHED |
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: Cornel Rasanga | Statement: [Siaya County, formerGovernor, Cornel Rasanga]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: formerGovernor Context triple: [Siaya County, formerGovernor, Cornel Rasanga]
-
A.
laterGovernor
Indicates that one entity subsequently became the governor of a place or jurisdiction associated with another entity.
-
B.
succeededInOfficeAsGovernorBy
Indicates that one individual’s term as governor ended and was directly followed by another individual’s term in the same office.
-
C.
hadGovernor
chosen
Indicates that an administrative region or political entity was governed by a specific person who held the office of governor.
-
D.
precededInOfficeAsGovernorBy
Indicates that one individual assumed the role of governor after another specific individual, who held the office immediately before them.
-
E.
lastGovernor
Indicates that one entity served as the most recent (final or current) governor of another entity, such as a region or territory.
- 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_69f34914dfc48190a390cd0720d9e86f |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69ff70ecc1a481909571b18d56d982b8 |
completed | May 9, 2026, 5:37 p.m. |
| PD | Predicate disambiguation | batch_69ff70322a3c8190837840ea42cd3093 |
completed | May 9, 2026, 5:34 p.m. |
Created at: May 1, 2026, 12:48 a.m.