Triple
T21625039
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | DE-RP |
E533678
|
entity |
| Predicate | subdivisionCodeLength |
P145262
|
FINISHED |
| Object | 2 |
—
|
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: 2 | Statement: [DE-RP, subdivisionCodeLength, 2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: subdivisionCodeLength Context triple: [DE-RP, subdivisionCodeLength, 2]
-
A.
hasSubdivisionCode
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.
subdivisionFactor
Indicates how many smaller parts or segments a whole entity is divided into within a given context.
-
D.
usesNumericSubdivisionCode
Indicates that one entity employs a numeric subdivision code system to identify or classify parts or regions of another entity.
-
E.
subdivisionUnitOf
Indicates that one administrative or organizational unit functions as a smaller constituent part within a larger unit.
- F. None of above. chosen
Provenance (4 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_69e0c464fba881908d0ff2ac80511ce1 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ef52121c3c8190b9b4d862ed247c71 |
completed | April 27, 2026, 12:09 p.m. |
| PD | Predicate disambiguation | batch_69e69677b9c48190bf81f795aa8ad74e |
completed | April 20, 2026, 9:11 p.m. |
| PDg | Predicate description generation | batch_69e69cb4bcbc8190a4fc2d508df107be |
completed | April 20, 2026, 9:37 p.m. |
Created at: April 16, 2026, 6:34 p.m.