Triple
T15714864
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shikaribetsu Onsen |
E380934
|
entity |
| Predicate | onsenArea |
P119892
|
FINISHED |
| Object | Tokachi onsen region |
—
|
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: Tokachi onsen region | Statement: [Shikaribetsu Onsen, onsenArea, Tokachi onsen region]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: onsenArea Context triple: [Shikaribetsu Onsen, onsenArea, Tokachi onsen region]
-
A.
HovdenIs
Indicates that something or someone is identified as, characterized as, or located in Hovden.
-
B.
designedArea
Indicates that an area has been intentionally planned, shaped, or configured according to a specific design or purpose.
-
C.
andraChansenCity
Indicates that a given city is the location where the "Andra Chansen" (Second Chance) round of a competition takes place.
-
D.
fareArea
Indicates the geographic or zonal region within which a particular fare or pricing rule applies.
-
E.
coreAreaOf
Indicates that one entity is the central, primary, or most important area or domain of focus for another 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_69d86d9bf930819082b30cf6d169297c |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e04f90aea0819082a9e9fe0f7780b0 |
completed | April 16, 2026, 2:55 a.m. |
| PD | Predicate disambiguation | batch_69e00526759c819088b80d85138b8974 |
completed | April 15, 2026, 9:37 p.m. |
| PDg | Predicate description generation | batch_69e0094af5b481908ad51d5d7ba0c726 |
completed | April 15, 2026, 9:55 p.m. |
Created at: April 10, 2026, 4:45 a.m.