Triple
T32472676
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Executive branch of Iran |
E829886
|
entity |
| Predicate | presidentialTermLimit |
P541
|
FINISHED |
| Object | two consecutive terms |
—
|
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: two consecutive terms | Statement: [Executive branch of Iran, presidentialTermLimit, two consecutive terms]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: presidentialTermLimit Context triple: [Executive branch of Iran, presidentialTermLimit, two consecutive terms]
-
A.
incumbentPresidentTermLimitReason
Indicates the reason why the current president is subject to a specific term limit or restriction on holding office.
-
B.
incumbentTermLimited
Indicates that the current officeholder is restricted by term limits from serving another consecutive term in that office.
-
C.
presidentialTerm
Indicates the period of time during which an individual officially serves as president of a country or organization.
-
D.
termLimitDefinedBy
chosen
Indicates that the duration or number of terms for holding a position is specified or constrained by a particular rule, law, or authority.
-
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_69f3491ee87c81908cbf5890079c2af6 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6d74b20a48190900dda1014cc13a8 |
completed | May 3, 2026, 5:04 a.m. |
| PD | Predicate disambiguation | batch_69f6d26f27dc8190ae426a3e1573933e |
completed | May 3, 2026, 4:43 a.m. |
Created at: May 1, 2026, 12:57 a.m.