Triple
T6389733
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kameoka |
E143790
|
entity |
| Predicate | populationRegionType |
P70326
|
FINISHED |
| Object | suburban-rural |
—
|
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: suburban-rural | Statement: [Kameoka, populationRegionType, suburban-rural]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: populationRegionType Context triple: [Kameoka, populationRegionType, suburban-rural]
-
A.
populationRegion
Indicates that a specified population is located within or associated with a particular geographic region.
-
B.
politicalRegionType
Indicates the classification of a political region according to its governmental or administrative type (e.g., state, province, municipality).
-
C.
geographicalRegionType
Indicates the specific kind or category of geographical region that an entity belongs to (e.g., continent, country, province, or city).
-
D.
demographicRegion
Indicates that an entity is associated with, belongs to, or is characterized by a particular geographic or administrative region for demographic purposes.
-
E.
placeRegion
Indicates that a place is located within, or is part of, a larger geographic or administrative region.
- 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_69c008db906c819096f3597d55d95432 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0686cc6d481909c62a29a84a4ce8e |
completed | March 22, 2026, 10:08 p.m. |
| PD | Predicate disambiguation | batch_69c060eff524819094cee1c70a0c1ff4 |
completed | March 22, 2026, 9:36 p.m. |
| PDg | Predicate description generation | batch_69c0623d23448190a75cf5d802fc0a02 |
completed | March 22, 2026, 9:42 p.m. |
Created at: March 22, 2026, 4:34 p.m.