Triple
T35983917
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | OIMM |
E1040653
|
entity |
| Predicate | countryCodePrefixRepresents |
—
|
GENERATED |
| Object | Iran in ICAO location indicators |
—
|
UNRECOGNIZED GENERATED |
How this triple was built (1 step)
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.
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: countryCodePrefixRepresents Context triple: [OIMM, countryCodePrefixRepresents, Iran in ICAO location indicators]
-
A.
associatedCountryCodePrefix
chosen
Indicates that one entity has a country code prefix that is associated with, or corresponds to, the other entity.
-
B.
continentCode
Indicates the standardized code assigned to the continent with which an entity is associated.
-
C.
countryCodeMeaning
Indicates the semantic meaning or description associated with a given country code.
-
D.
mobileNumberPrefix
Indicates that one entity is a telephone number prefix associated with, or used to begin, the other entity’s mobile phone numbers.
-
E.
numericCountryCode
Indicates that a country is associated with a specific numeric code that uniquely identifies it.
- F. None of above.
Provenance (1 batch)
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_69f76e28293c8190ae3f4e2208b87117 |
completed | May 3, 2026, 3:47 p.m. |
Created at: May 3, 2026, 4:07 p.m.