Triple
T21593676
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Flag of Iran |
E532841
|
entity |
| Predicate | totalScriptRepetitions |
P25594
|
FINISHED |
| Object | 22 |
—
|
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: 22 | Statement: [Flag of Iran, totalScriptRepetitions, 22]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: totalScriptRepetitions Context triple: [Flag of Iran, totalScriptRepetitions, 22]
-
A.
repetitionCount
chosen
Indicates the number of times a particular event, action, or pattern is repeated within a given context.
-
B.
repetitionOf
Indicates that one entity is a repeated occurrence or instance of another entity, preserving the same content or pattern.
-
C.
usesRepetition
Indicates that one entity employs repeated elements, actions, or patterns as a deliberate feature or technique in relation to another entity or context.
-
D.
numberOfExecutions
Indicates the count of times a particular action, process, or event has been carried out.
-
E.
hasRepetition
Indicates that something occurs, appears, or is performed more than once, showing recurrence or repeated instances within a given context.
- 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_69e0c46251648190876f0427cf2d321b |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69eefadf6e608190b42b26ea22c76ec6 |
completed | April 27, 2026, 5:57 a.m. |
| PD | Predicate disambiguation | batch_69e632109d048190b4ac3f14fe48d1a0 |
completed | April 20, 2026, 2:02 p.m. |
Created at: April 16, 2026, 6:32 p.m.