Triple
T14282806
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bogra Formula |
E354091
|
entity |
| Predicate | primeMinisterTermLength |
P54275
|
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: [Bogra Formula, primeMinisterTermLength, 5 years]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primeMinisterTermLength Context triple: [Bogra Formula, primeMinisterTermLength, 5 years]
-
A.
primeMinisterTerm
chosen
Indicates the period of time during which a person holds the office and exercises the role of prime minister of a government.
-
B.
primeMinisterTermEnd
Indicates the date or point in time when a person's tenure as prime minister comes to an end.
-
C.
numberOfTermsAsPrimeMinister
Indicates how many separate terms an individual has served in the role of prime minister.
-
D.
primeMinisterTermStart
Indicates the date on which an individual officially begins serving as prime minister.
-
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_69d8278d25148190abf1a8c8f5f533ad |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de697d9fd08190b0cd7a6a6737ba03 |
completed | April 14, 2026, 4:21 p.m. |
| PD | Predicate disambiguation | batch_69de2a88446481909cd526da97a3b70f |
completed | April 14, 2026, 11:52 a.m. |
Created at: April 10, 2026, 1:10 a.m.