Triple
T15906374
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ISO 3166-2:JO |
E385730
|
entity |
| Predicate | hasSubdivisionCodeExample |
P22016
|
FINISHED |
| Object | JO-AM |
—
|
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: JO-AM | Statement: [ISO 3166-2:JO, hasSubdivisionCodeExample, JO-AM]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSubdivisionCodeExample Context triple: [ISO 3166-2:JO, hasSubdivisionCodeExample, JO-AM]
-
A.
hasSubdivisionCode
chosen
Indicates that an entity is associated with a specific code identifying one of its internal subdivisions (such as a state, province, or region).
-
B.
hasSubdivisionCodePart
Indicates that an entity’s subdivision code includes or is composed of the referenced code segment or component.
-
C.
hasSubdivisionExample
Indicates that one entity is an example or instance of a subdivision or component part of another entity.
-
D.
hasSubdivisionCodeContext
Indicates that a subdivision code is interpreted within a specific coding or contextual framework that defines its meaning.
-
E.
hasSubdivision
Indicates that one entity is divided into and contains another entity as one of its constituent parts or administrative units.
- 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_69d86da686e4819097cbf3b1fc2d881d |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e17d4d08f481909f38b75e3f42d9ab |
completed | April 17, 2026, 12:22 a.m. |
| PD | Predicate disambiguation | batch_69e142ca3b208190946c3aa4c1e6087c |
completed | April 16, 2026, 8:12 p.m. |
Created at: April 10, 2026, 4:52 a.m.