Triple
T9235186
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SA-08 |
E221918
|
entity |
| Predicate | codeComponentSubdivision |
P54482
|
FINISHED |
| Object | 08 |
—
|
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: 08 | Statement: [SA-08, codeComponentSubdivision, 08]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: codeComponentSubdivision Context triple: [SA-08, codeComponentSubdivision, 08]
-
A.
countrySubdivision
Indicates that one geopolitical region is an administrative or territorial subdivision of a larger country.
-
B.
hasSubdivisionCodePart
chosen
Indicates that an entity’s subdivision code includes or is composed of the referenced code segment or component.
-
C.
hasSubdivisionCode
Indicates that an entity is associated with a specific code identifying one of its internal subdivisions (such as a state, province, or region).
-
D.
countrySubdivisionType
Indicates the specific type or category of an administrative or territorial subdivision within a country (e.g., state, province, region).
-
E.
associatedCountrySubdivisionCode
Indicates the specific administrative region or subdivision code within a country that is linked to or relevant for the given entity.
- 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_69ca83ed628c8190bc02d641e57f097f |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69ccee1cca0c8190bf587f54236c9e45 |
completed | April 1, 2026, 10:06 a.m. |
| PD | Predicate disambiguation | batch_69cc7a4765648190aa9445c4a22dc471 |
completed | April 1, 2026, 1:52 a.m. |
Created at: March 30, 2026, 7:29 p.m.