Triple
T30229795
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kenyan general elections |
E768594
|
entity |
| Predicate | termLengthCountyGovernment |
P33746
|
FINISHED |
| Object | 5 years |
—
|
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: 5 years | Statement: [Kenyan general elections, termLengthCountyGovernment, 5 years]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: termLengthCountyGovernment Context triple: [Kenyan general elections, termLengthCountyGovernment, 5 years]
-
A.
termLength
Indicates the duration or period of time for which an agreement, position, or condition remains in effect.
-
B.
termLengthNumber
chosen
Indicates the numerical value representing the duration or length of a specified term.
-
C.
termLengthCharacteristic
Indicates the specific duration-related property or feature associated with a term (such as its length or time span).
-
D.
electsTermLength
Indicates the length of time for which an entity is elected to hold a particular position or office.
-
E.
governorTerm
Indicates the time period during which a person holds or held the office of governor of a specific jurisdiction.
- 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_69f2248108208190be60bf1af343ce70 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f6802486ac8190a936df82f2988383 |
completed | May 2, 2026, 10:52 p.m. |
| PD | Predicate disambiguation | batch_69f6760216108190bbb708d53a6c2c25 |
completed | May 2, 2026, 10:09 p.m. |
Created at: April 29, 2026, 7:36 p.m.