Triple
T464218
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Izumi |
E8408
|
entity |
| Predicate | hasPostalSystem |
P14969
|
FINISHED |
| Object | Japanese postal system |
—
|
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: Japanese postal system | Statement: [Izumi, hasPostalSystem, Japanese postal system]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPostalSystem Context triple: [Izumi, hasPostalSystem, Japanese postal system]
-
A.
postalCodeSystem
Indicates a system that assigns structured postal codes to geographic areas for organizing and routing mail.
-
B.
hasPostalCodePrefix
Indicates that a location’s postal code begins with a specified sequence of characters.
-
C.
postalCode
Indicates the numerical or alphanumerical code assigned to a geographic area for mail delivery associated with an entity.
-
D.
postalCounty
Indicates the county associated with an entity for postal addressing or mail delivery purposes.
-
E.
postalArea
Indicates that one entity is the postal or ZIP code area associated with the location or address represented by the other entity.
- 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_69a2e7f3aeb48190a19453e3a043f486 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2efd5b6b48190ae23968135cf6417 |
completed | Feb. 28, 2026, 1:38 p.m. |
| PD | Predicate disambiguation | batch_69a2edea1acc81908a72d9f4c43438ea |
completed | Feb. 28, 2026, 1:30 p.m. |
| PDg | Predicate description generation | batch_69a2ef611b9c8190ac5e9174744d9127 |
completed | Feb. 28, 2026, 1:36 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.