Triple
T22233350
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jim Fouché |
E549523
|
entity |
| Predicate | termLengthAsStatePresident |
P540
|
FINISHED |
| Object | 7 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: 7 years | Statement: [Jim Fouché, termLengthAsStatePresident, 7 years]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: termLengthAsStatePresident Context triple: [Jim Fouché, termLengthAsStatePresident, 7 years]
-
A.
presidentialTerm
Indicates the period of time during which an individual officially serves as president of a country or organization.
-
B.
termLength
chosen
Indicates the duration or period of time for which an agreement, position, or condition remains in effect.
-
C.
numberOfTermInOffice
Indicates the specific ordinal count of how many terms an entity has served in a particular office or position.
-
D.
electsTermLength
Indicates the length of time for which an entity is elected to hold a particular position or office.
-
E.
timePeriodOfUseAsPresidentialOffice
Indicates the span of time during which a particular place or building was used as a presidential 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_69e11e4102b881909cf47d3768e25c19 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f12bf4e0348190b755a9ac0bc96cdd |
completed | April 28, 2026, 9:51 p.m. |
| PD | Predicate disambiguation | batch_69e71b5177d881908f90abde14ada7dc |
completed | April 21, 2026, 6:38 a.m. |
Created at: April 16, 2026, 8:38 p.m.