Triple
T37525002
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fourth Republic of Ghana |
E932884
|
entity |
| Predicate | hasPresidentialTermLength |
P39902
|
FINISHED |
| Object | 4 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: 4 years | Statement: [Fourth Republic of Ghana, hasPresidentialTermLength, 4 years]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPresidentialTermLength Context triple: [Fourth Republic of Ghana, hasPresidentialTermLength, 4 years]
-
A.
spansPresidentialTerm
Indicates that an event, period, or entity extends across the duration of a specified presidential term, covering at least part of that term.
-
B.
presidentialTerm
Indicates the period of time during which an individual officially serves as president of a country or organization.
-
C.
maximumConsecutiveTermsOfGovernor
Indicates the highest number of consecutive terms that a governor is allowed to serve in office.
-
D.
electsTermLength
chosen
Indicates the length of time for which an entity is elected to hold a particular position or office.
-
E.
numberOfTermInOffice
Indicates the specific ordinal count of how many terms an entity has served in a particular office or position.
- 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_69f76ec8862c8190bfa24145f5480642 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_6a037c8efcd4819088c2aeead65d93df |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a1553e08190bb7424c448cb1f33 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:17 p.m.