Triple
T26626365
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Onekotan Island |
E668358
|
entity |
| Predicate | administrativeCenterDistance |
P175302
|
FINISHED |
| Object | remote from Yuzhno-Sakhalinsk |
—
|
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: remote from Yuzhno-Sakhalinsk | Statement: [Onekotan Island, administrativeCenterDistance, remote from Yuzhno-Sakhalinsk]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: administrativeCenterDistance Context triple: [Onekotan Island, administrativeCenterDistance, remote from Yuzhno-Sakhalinsk]
-
A.
distanceFromRegionalCapital
Indicates the measured spatial distance between a given place and its corresponding regional capital.
-
B.
municipalityCenterDistance
Indicates the distance between an entity and the central point of its corresponding municipality.
-
C.
roadDistanceToCityCentre_km
Indicates the distance in kilometers from a location to the city centre when traveling by road.
-
D.
distanceToProvinceCapital_km
Indicates the distance, measured in kilometers, between a given location and the capital city of its province.
-
E.
administrativeCentreNearby
Indicates that an administrative centre is located close to the referenced entity in geographic or spatial terms.
- 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_69ee9cff507c819092b95bf7219a702e |
completed | April 26, 2026, 11:17 p.m. |
| NER | Named-entity recognition | batch_69f6d1d916f881909575c2b22c416a5b |
completed | May 3, 2026, 4:40 a.m. |
| PD | Predicate disambiguation | batch_69f6cfe2183481908ae4e85a59c66f69 |
completed | May 3, 2026, 4:32 a.m. |
| PDg | Predicate description generation | batch_69f6d0d331dc8190be5aa6bfc6365e67 |
completed | May 3, 2026, 4:36 a.m. |
Created at: April 27, 2026, 2:23 a.m.