Triple
T29672590
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jubilee Party of Kenya |
E750714
|
entity |
| Predicate | heldOfficeOfDeputyPresident |
P161796
|
FINISHED |
| Object | William Ruto |
—
|
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: William Ruto | Statement: [Jubilee Party of Kenya, heldOfficeOfDeputyPresident, William Ruto]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: heldOfficeOfDeputyPresident Context triple: [Jubilee Party of Kenya, heldOfficeOfDeputyPresident, William Ruto]
-
A.
wasDeputyIn
chosen
Indicates that an entity served in the role of deputy within a specified organization, office, or jurisdiction during a particular period.
-
B.
servedAsVicePresidentFrom
Indicates that one entity held the position of vice president for another entity during a specified time period.
-
C.
servesAsVicePresidentDuring
Indicates that one entity holds the position of vice president for another entity during a specified time period.
-
D.
succeededAsVicePresidentBy
Indicates that one individual ceased serving as vice president and was followed in that office by another specific individual.
-
E.
leftOfficeAsVicePresident
Indicates that an individual ceased holding the position of vice president, marking the end of their term in that office.
- 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_69f0d624d7b08190ba237d226f78d0d9 |
completed | April 28, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69f672598730819093b766fd418e1c08 |
completed | May 2, 2026, 9:53 p.m. |
| PD | Predicate disambiguation | batch_69f66abfdaf08190a55f14c70be6fd4d |
completed | May 2, 2026, 9:21 p.m. |
Created at: April 28, 2026, 7:05 p.m.